Contributed by:

The main objective of this research is to identify the effectiveness of the e-learning method in the teaching of mathematics with adults who are in high school, in contrast to the traditional expository method. The study developed is quantitative, descriptive, and correlational. The research design is quasi-experimental, with a control group and an experimental group.

1.
mathematics

E-Learning in the Teaching of Mathematics: An

Educational Experience in Adult High School

Antonio-José Moreno-Guerrero , Inmaculada Aznar-Díaz , Pilar Cáceres-Reche and

Santiago Alonso-García *

Department of Didactics and School Organization, University of Granada, 18071 Granada, Spain;

[email protected] (A.-J.M.-G.); [email protected] (I.A.-D.); [email protected] (P.C.-R.)

* Correspondence: [email protected]

Received: 29 April 2020; Accepted: 21 May 2020; Published: 22 May 2020

Abstract: Currently, the e-learning method, due to the period of confinement that is occurring

due to COVID-19, has increased its use and application in the teaching and learning processes.

The main objective of this research is to identify the effectiveness of the e-learning method in the

teaching of mathematics with adults who are in high school, in contrast to the traditional expository

method. The study developed is quantitative, descriptive and correlational. The research design is

quasi-experimental, with a control group and an experimental group. The results show that the use of

the e-learning method has a positive influence on motivation, autonomy, participation, mathematical

concepts, results and grades. It can be concluded that the e-learning method leads to improvement in

adult students who are studying the mathematical subject in the educational stage of high school,

provided that it is compared with the expository method. Therefore, this method is considered

effective for its implementation in adults.

Keywords: emerging methodology; educational innovation; e-learning; educational experimentation;

adults; students

1. Introduction

Technological development is a reality today [1]. This fact is reflected in our society [2], specifically

in the labour, social and educational fields [3]. This technological advance facilitates, strengthens and

speeds up the performance of daily tasks [4].

In the educational field, technological progress is reflected in the development of the so-called

information and communication technologies (ICT) [5]. ICTs directly influence the development

of teaching and learning processes [6], since they promote innovative pedagogical actions, as well

as generate new learning spaces [7]. These pedagogical events enhance the transformation of the

classroom as we know it [8], since they allow for the elimination of spatial-temporal barriers [9], as well

as access to a large amount of information [10], with different formats [11]. It has also promoted

the improvement of students’ motivation, autonomy, involvement and attitude towards educational

content [12–14].

Among the pedagogical actions based on ICTs is e-learning, which is defined as the pedagogical

act that takes place online, thanks to the use of the Internet and technological devices, whether mobile or

not, with synchronous or asynchronous connection, and from anywhere [15]. Therefore, the e-learning

method becomes a pedagogical tool that facilitates access to learning for the whole of society [16].

The method of not is of recent creation [17], since its beginnings date back to 1993, when it began

to be used more assiduously, having a greater impact in the field of education [18]. Prior to that date,

distance learning was widely used.

Mathematics 2020, 8, 840; doi:10.3390/math8050840 www.mdpi.com/journal/mathematics

E-Learning in the Teaching of Mathematics: An

Educational Experience in Adult High School

Antonio-José Moreno-Guerrero , Inmaculada Aznar-Díaz , Pilar Cáceres-Reche and

Santiago Alonso-García *

Department of Didactics and School Organization, University of Granada, 18071 Granada, Spain;

[email protected] (A.-J.M.-G.); [email protected] (I.A.-D.); [email protected] (P.C.-R.)

* Correspondence: [email protected]

Received: 29 April 2020; Accepted: 21 May 2020; Published: 22 May 2020

Abstract: Currently, the e-learning method, due to the period of confinement that is occurring

due to COVID-19, has increased its use and application in the teaching and learning processes.

The main objective of this research is to identify the effectiveness of the e-learning method in the

teaching of mathematics with adults who are in high school, in contrast to the traditional expository

method. The study developed is quantitative, descriptive and correlational. The research design is

quasi-experimental, with a control group and an experimental group. The results show that the use of

the e-learning method has a positive influence on motivation, autonomy, participation, mathematical

concepts, results and grades. It can be concluded that the e-learning method leads to improvement in

adult students who are studying the mathematical subject in the educational stage of high school,

provided that it is compared with the expository method. Therefore, this method is considered

effective for its implementation in adults.

Keywords: emerging methodology; educational innovation; e-learning; educational experimentation;

adults; students

1. Introduction

Technological development is a reality today [1]. This fact is reflected in our society [2], specifically

in the labour, social and educational fields [3]. This technological advance facilitates, strengthens and

speeds up the performance of daily tasks [4].

In the educational field, technological progress is reflected in the development of the so-called

information and communication technologies (ICT) [5]. ICTs directly influence the development

of teaching and learning processes [6], since they promote innovative pedagogical actions, as well

as generate new learning spaces [7]. These pedagogical events enhance the transformation of the

classroom as we know it [8], since they allow for the elimination of spatial-temporal barriers [9], as well

as access to a large amount of information [10], with different formats [11]. It has also promoted

the improvement of students’ motivation, autonomy, involvement and attitude towards educational

content [12–14].

Among the pedagogical actions based on ICTs is e-learning, which is defined as the pedagogical

act that takes place online, thanks to the use of the Internet and technological devices, whether mobile or

not, with synchronous or asynchronous connection, and from anywhere [15]. Therefore, the e-learning

method becomes a pedagogical tool that facilitates access to learning for the whole of society [16].

The method of not is of recent creation [17], since its beginnings date back to 1993, when it began

to be used more assiduously, having a greater impact in the field of education [18]. Prior to that date,

distance learning was widely used.

Mathematics 2020, 8, 840; doi:10.3390/math8050840 www.mdpi.com/journal/mathematics

2.
Mathematics 2020, 8, 840 2 of 16

This method of teaching is currently on the rise due to COVID-19 [19]. Its flexibility in terms of

location, time, effort and costs [20], makes it the most appropriate option for training and evaluating

students [21].

It should be borne in mind that two types of resources are required to develop the e-learning

method: digital and technological [22]. Among the digital resources are educational videos, teaching

platforms, videoconferences, podcasts, social networks, among many other resources [23]. While

technological resources can be the desktop computer, tablet, smartphone, among others [24].

The use of e-learning by the members involved in the teaching and learning process becomes a

challenge [17], because an average level of digital competence is required to apply it with guarantees [25].

Therefore, teachers and students need to be trained in the use of the various technological and digital

resources [26].

This teaching method has a number of characteristics that make it different from other teaching

methods [27]. Some authors see it as an evolution of distance education [28,29]. For others, it is a new

teaching modality that differs substantially from face-to-face teaching [30].

Be that as it may, e-learning has a number of characteristics, among which are promoting dialogue

and group activities, enhancing students’ interpersonal relations [31]; encouraging collaboration

among students themselves, achieving joint goals in the elaboration of different tasks [29]; facilitating

communication, both synchronous and asynchronous [32]; enabling learning to take place from any

location, provided that a technological device is available [33] to encourage the acquisition of digital

competence in students [34]; enable adaptation to the individual pace of students [35]; enhance

motivation, as the student can develop his or her own learning style [36]; promote the acquisition of

learning to learn competence [37]; be adapted to the circumstances of each individual, both personal

and occupational [38]; provide access to an unlimited amount of learning resources [39]; facilitate

teacher monitoring of student activity [40]; and promote student familiarisation with the use of

technological and digital resources [41].

It should also be noted that the e-learning method is a special case of distance learning [42].

There are several reasons for this [43]. In distance learning, email is used to receive the contents of

the subject, not having a virtual medium [44]. In addition, a large number of theoretical contents are

presented, which are not interactive and whose sequencing is closed [45]. Additionally, contact with

the teacher is sporadic, which acts as a mere transmitter of content. In this case, the student is a passive

receiver, who usually has a feeling of loneliness [46].

In other words, the teaching-learning process can take place 24 hours per day, every day of the

year [47], allowing students to be trained while they are on the move or in a place other than their usual

one [48], promoting a change in the teacher-learner mentality, and with it the philosophy of learning,

in which the student organizes his or her training process and the teacher guides that action [49],

and allowing unlimited access to network resources [50]. Therefore, the use of e-learning totally

changes the perspective we had of teaching until now [51].

However, the e-learning method can generate a spatial and temporal gap [52], so it is necessary

to personalize the educational experience of the students, trying to keep the learners motivated and

committed [53]. Moreover, in developing countries, the use of ICT is not as widespread as in developed

countries, leading to a lack of acceptance of technological resources and, therefore, of e-learning, not

having the desired effect on educational learning [54,55].

Mathematics in the field of social sciences is considered a necessary instrument to be able to

decipher the closest environment and represent various facts, be they social, scientific and technical

that occur in today’s world [56]. Mathematics facilitate the understanding of various phenomena, be it

social reality itself, economic aspects or historical facts, among others [57]. In this case, mathematics

becomes an adequate tool to acquire knowledge, reflect on social aspects, and represent facts from

the environment [58]. In other words, mathematics tries to convert all these facts into knowledge and

information [59]. In addition, the language used in the mathematical field allows the phenomena that

occur to be explained in detail and precisely [60].

This method of teaching is currently on the rise due to COVID-19 [19]. Its flexibility in terms of

location, time, effort and costs [20], makes it the most appropriate option for training and evaluating

students [21].

It should be borne in mind that two types of resources are required to develop the e-learning

method: digital and technological [22]. Among the digital resources are educational videos, teaching

platforms, videoconferences, podcasts, social networks, among many other resources [23]. While

technological resources can be the desktop computer, tablet, smartphone, among others [24].

The use of e-learning by the members involved in the teaching and learning process becomes a

challenge [17], because an average level of digital competence is required to apply it with guarantees [25].

Therefore, teachers and students need to be trained in the use of the various technological and digital

resources [26].

This teaching method has a number of characteristics that make it different from other teaching

methods [27]. Some authors see it as an evolution of distance education [28,29]. For others, it is a new

teaching modality that differs substantially from face-to-face teaching [30].

Be that as it may, e-learning has a number of characteristics, among which are promoting dialogue

and group activities, enhancing students’ interpersonal relations [31]; encouraging collaboration

among students themselves, achieving joint goals in the elaboration of different tasks [29]; facilitating

communication, both synchronous and asynchronous [32]; enabling learning to take place from any

location, provided that a technological device is available [33] to encourage the acquisition of digital

competence in students [34]; enable adaptation to the individual pace of students [35]; enhance

motivation, as the student can develop his or her own learning style [36]; promote the acquisition of

learning to learn competence [37]; be adapted to the circumstances of each individual, both personal

and occupational [38]; provide access to an unlimited amount of learning resources [39]; facilitate

teacher monitoring of student activity [40]; and promote student familiarisation with the use of

technological and digital resources [41].

It should also be noted that the e-learning method is a special case of distance learning [42].

There are several reasons for this [43]. In distance learning, email is used to receive the contents of

the subject, not having a virtual medium [44]. In addition, a large number of theoretical contents are

presented, which are not interactive and whose sequencing is closed [45]. Additionally, contact with

the teacher is sporadic, which acts as a mere transmitter of content. In this case, the student is a passive

receiver, who usually has a feeling of loneliness [46].

In other words, the teaching-learning process can take place 24 hours per day, every day of the

year [47], allowing students to be trained while they are on the move or in a place other than their usual

one [48], promoting a change in the teacher-learner mentality, and with it the philosophy of learning,

in which the student organizes his or her training process and the teacher guides that action [49],

and allowing unlimited access to network resources [50]. Therefore, the use of e-learning totally

changes the perspective we had of teaching until now [51].

However, the e-learning method can generate a spatial and temporal gap [52], so it is necessary

to personalize the educational experience of the students, trying to keep the learners motivated and

committed [53]. Moreover, in developing countries, the use of ICT is not as widespread as in developed

countries, leading to a lack of acceptance of technological resources and, therefore, of e-learning, not

having the desired effect on educational learning [54,55].

Mathematics in the field of social sciences is considered a necessary instrument to be able to

decipher the closest environment and represent various facts, be they social, scientific and technical

that occur in today’s world [56]. Mathematics facilitate the understanding of various phenomena, be it

social reality itself, economic aspects or historical facts, among others [57]. In this case, mathematics

becomes an adequate tool to acquire knowledge, reflect on social aspects, and represent facts from

the environment [58]. In other words, mathematics tries to convert all these facts into knowledge and

information [59]. In addition, the language used in the mathematical field allows the phenomena that

occur to be explained in detail and precisely [60].

3.
Mathematics 2020, 8, 840 3 of 16

It should be borne in mind that mathematics is instrumental, and is the basis for acquiring

knowledge from other subjects, or in other fields, such as sociology or political science [61].

In addition, mathematics develops the student’s intellect, promoting competencies that will allow

him to function personally and socially [62]. It also promotes creativity, the development of autonomy,

the improvement of self-esteem and entrepreneurship [63].

In the field of mathematics, there are educational actions in which e-learning has been developed

as a teaching method [64,65]. One of the ideas is that applied in the MCIEC model (motivation, context,

interactivity, evaluation and connectivity), which entails greater student involvement. This model

allows the student to increase his or her ability to make an effort to understand mathematical content,

thanks to increased interest, motivation and adaptation to the context [64]. The development of

the e-learning method presents improvements if it is applied with an appropriate teaching and

learning method. An example of this is the development of the e-learning method associated with

the GeoGebra resource, which is integrated into the Moodle platform, improving aspects related

to assessment, motivation and student interest. It also promotes learning in a more meaningful

way and adapts assessment to students’ needs [65]. Another similar case is that of the Working

Memory Capacity (WMC) method, developed in the e-learning method. This method leads to an

improvement in students’ abilities to acquire various mathematical concepts. In this case, it improves

students’ academic performance. This is due to the increase of their involvement and motivation in

mathematical contents [66]. Another case is the development of the e-learning method, associated

with the Edmodo application, in the field of mathematics. This training process increases participation

in learning. This involvement increases the memorization, comprehension, application, analysis,

evaluation and creation of mathematical contents. It also increases students’ attitude and acceptance

of mathematical content [67]. The use of e-learning in the development of mathematics increases

the commitment of students themselves, improving performance. It also increases interest, and thus,

acquired results. It also improves the acquisition of mathematical content [68]. Another example

is pedagogical action, in which e-learning is used with the individualized e-learning environment

called UZWEBMAT. This combination promotes individualized attention of students. Moreover, it is

adapted to the learning style of the students, improving their comprehension skills. It also increases

their responsibility for learning and is reflected in motivation and academic performance [69]. In many

cases, student learning, and therefore student outcomes, can be affected by poor connectivity, inflexible

scheduling, and inadequate devices [70].

2. Justification and Research Objectives

The use of ICTs today, coupled with the global crisis being experienced by COVID-19, makes

e-learning a necessary teaching method. This implies the application of new didactic strategies and

pedagogical approaches [71].

This study presents a teaching method based on e-learning for adult students who study high

school in the distance mode. In addition, it shows the pedagogical actions developed during the first

quarter of the 2019–2020 school year. A contrast is also established with the traditional expository

method developed with the students of the night school. All of this was done in the subject of

mathematics applied to the social sciences.

The aim of this research is to give continuity to the application of the e-learning method in the

teaching of mathematics, with the intention of contrasting the results obtained in other studies with

similar characteristics [63–70].

The main objective of this research is to identify the effectiveness of the e-learning method in

teaching mathematics to adults who are in high school, in contrast to the traditional expository method.

The following specific objectives are established from this objective:

• Determine the degree of motivation;

• Identify the degree of autonomy;

• Analyse the level of collaboration;

It should be borne in mind that mathematics is instrumental, and is the basis for acquiring

knowledge from other subjects, or in other fields, such as sociology or political science [61].

In addition, mathematics develops the student’s intellect, promoting competencies that will allow

him to function personally and socially [62]. It also promotes creativity, the development of autonomy,

the improvement of self-esteem and entrepreneurship [63].

In the field of mathematics, there are educational actions in which e-learning has been developed

as a teaching method [64,65]. One of the ideas is that applied in the MCIEC model (motivation, context,

interactivity, evaluation and connectivity), which entails greater student involvement. This model

allows the student to increase his or her ability to make an effort to understand mathematical content,

thanks to increased interest, motivation and adaptation to the context [64]. The development of

the e-learning method presents improvements if it is applied with an appropriate teaching and

learning method. An example of this is the development of the e-learning method associated with

the GeoGebra resource, which is integrated into the Moodle platform, improving aspects related

to assessment, motivation and student interest. It also promotes learning in a more meaningful

way and adapts assessment to students’ needs [65]. Another similar case is that of the Working

Memory Capacity (WMC) method, developed in the e-learning method. This method leads to an

improvement in students’ abilities to acquire various mathematical concepts. In this case, it improves

students’ academic performance. This is due to the increase of their involvement and motivation in

mathematical contents [66]. Another case is the development of the e-learning method, associated

with the Edmodo application, in the field of mathematics. This training process increases participation

in learning. This involvement increases the memorization, comprehension, application, analysis,

evaluation and creation of mathematical contents. It also increases students’ attitude and acceptance

of mathematical content [67]. The use of e-learning in the development of mathematics increases

the commitment of students themselves, improving performance. It also increases interest, and thus,

acquired results. It also improves the acquisition of mathematical content [68]. Another example

is pedagogical action, in which e-learning is used with the individualized e-learning environment

called UZWEBMAT. This combination promotes individualized attention of students. Moreover, it is

adapted to the learning style of the students, improving their comprehension skills. It also increases

their responsibility for learning and is reflected in motivation and academic performance [69]. In many

cases, student learning, and therefore student outcomes, can be affected by poor connectivity, inflexible

scheduling, and inadequate devices [70].

2. Justification and Research Objectives

The use of ICTs today, coupled with the global crisis being experienced by COVID-19, makes

e-learning a necessary teaching method. This implies the application of new didactic strategies and

pedagogical approaches [71].

This study presents a teaching method based on e-learning for adult students who study high

school in the distance mode. In addition, it shows the pedagogical actions developed during the first

quarter of the 2019–2020 school year. A contrast is also established with the traditional expository

method developed with the students of the night school. All of this was done in the subject of

mathematics applied to the social sciences.

The aim of this research is to give continuity to the application of the e-learning method in the

teaching of mathematics, with the intention of contrasting the results obtained in other studies with

similar characteristics [63–70].

The main objective of this research is to identify the effectiveness of the e-learning method in

teaching mathematics to adults who are in high school, in contrast to the traditional expository method.

The following specific objectives are established from this objective:

• Determine the degree of motivation;

• Identify the degree of autonomy;

• Analyse the level of collaboration;

4.
Mathematics 2020, 8, 840 4 of 16

• To know the degree of participation;

• To find out the level of problem solving;

• Determine the degree of class time;

• Identify the level of learning of concepts, graphs, scientific data and results;

• To know the capacity of decision in the pedagogical actions; and

• To find out the variation of grades.

3. Method of Investigation

3.1. Research Design and Data Analysis

The study developed is quantitative, descriptive and correlational [72]. The research design is

quasi-experimental, with a control group (GC) and an experimental group (Ge), that is, non-equivalent

groups. In this case, the research process developed in other previous studies has been followed,

where active teaching methods have been applied [73,74]. Unlike the investigations mentioned above,

this study tries to know how an active teaching method influences, in this case, the e-learning method

in the development of the development of the subject of mathematics. For this, a contrast is established

with the exhibition method. The students are divided into two groups: the control group, made up of

night school freshmen; and the experimental group, made up of distance school freshmen. In both

groups the subject of mathematics applied to social sciences has been developed. In the control group

the traditional expository method has been applied. In the experimental group the e-learning teaching

method has been developed. The distribution of the students has not been random, because the groups

have been formed by the head of studies, according to the registration requested by the students.

The criteria for the distribution of the student body is based on the principles of equity and equality.

In other words, the management team distributed the groups bearing in mind several criteria, including

the length of time the students have been out of official studies and the grades of the last year enrolled.

With respect to years of non-study, it established three criteria: (a) more than 10 years not enrolled in

official studies; (b) between 10 and 5 years not enrolled in official studies; (c) less than five years not

enrolled in official studies. With regard to the qualification, it established four criteria: (a) no subjects

passed in the last year enrolled; (b) between 0 and 3 subjects passed; (c) between 4 and 6 subjects

passed; (d) all subjects passed. Based on these criteria, it made an even distribution. These criteria are

set out in the School Education Project. The information was collected at the end of the first quarter,

that is, after the pedagogical intervention, through the application of a post-test (Table 1).

Table 1. Composition of the groups.

Group n Composition Pretest Treatment Posttest

1- Control 61 Natural - X1 O1

2- Experimental 71 Natural - X2 O2

The Statistical Package for the Social Sciences (SPSS) v25 (IBM Corp., Armonk, NY, USA) was used

to analyse the data collected. The statistics used are mean (M) and standard deviation, in addition to

skewness (Skw ) and kurtosis (Kme ) statistics. Additionally, Student’s t-test (tn1+n2−2 ) has been used to

compare the means between the established groups. Finally, Cohen’s d-test and the biserial correlation

(rxy ) have been applied, in order to know the effect size and the out-of-association. The significance

level applied in the study was p < 0.05.

3.2. Participants

The sample applied in this research consists of 132 students. The sampling technique applied is

for convenience. This is due to the ease of access to the students. In studies focused on the application

of pedagogical methods, the sample size is not a determining factor [75,76].

• To know the degree of participation;

• To find out the level of problem solving;

• Determine the degree of class time;

• Identify the level of learning of concepts, graphs, scientific data and results;

• To know the capacity of decision in the pedagogical actions; and

• To find out the variation of grades.

3. Method of Investigation

3.1. Research Design and Data Analysis

The study developed is quantitative, descriptive and correlational [72]. The research design is

quasi-experimental, with a control group (GC) and an experimental group (Ge), that is, non-equivalent

groups. In this case, the research process developed in other previous studies has been followed,

where active teaching methods have been applied [73,74]. Unlike the investigations mentioned above,

this study tries to know how an active teaching method influences, in this case, the e-learning method

in the development of the development of the subject of mathematics. For this, a contrast is established

with the exhibition method. The students are divided into two groups: the control group, made up of

night school freshmen; and the experimental group, made up of distance school freshmen. In both

groups the subject of mathematics applied to social sciences has been developed. In the control group

the traditional expository method has been applied. In the experimental group the e-learning teaching

method has been developed. The distribution of the students has not been random, because the groups

have been formed by the head of studies, according to the registration requested by the students.

The criteria for the distribution of the student body is based on the principles of equity and equality.

In other words, the management team distributed the groups bearing in mind several criteria, including

the length of time the students have been out of official studies and the grades of the last year enrolled.

With respect to years of non-study, it established three criteria: (a) more than 10 years not enrolled in

official studies; (b) between 10 and 5 years not enrolled in official studies; (c) less than five years not

enrolled in official studies. With regard to the qualification, it established four criteria: (a) no subjects

passed in the last year enrolled; (b) between 0 and 3 subjects passed; (c) between 4 and 6 subjects

passed; (d) all subjects passed. Based on these criteria, it made an even distribution. These criteria are

set out in the School Education Project. The information was collected at the end of the first quarter,

that is, after the pedagogical intervention, through the application of a post-test (Table 1).

Table 1. Composition of the groups.

Group n Composition Pretest Treatment Posttest

1- Control 61 Natural - X1 O1

2- Experimental 71 Natural - X2 O2

The Statistical Package for the Social Sciences (SPSS) v25 (IBM Corp., Armonk, NY, USA) was used

to analyse the data collected. The statistics used are mean (M) and standard deviation, in addition to

skewness (Skw ) and kurtosis (Kme ) statistics. Additionally, Student’s t-test (tn1+n2−2 ) has been used to

compare the means between the established groups. Finally, Cohen’s d-test and the biserial correlation

(rxy ) have been applied, in order to know the effect size and the out-of-association. The significance

level applied in the study was p < 0.05.

3.2. Participants

The sample applied in this research consists of 132 students. The sampling technique applied is

for convenience. This is due to the ease of access to the students. In studies focused on the application

of pedagogical methods, the sample size is not a determining factor [75,76].

5.
Mathematics 2020, 8, 840 5 of 16

The students are studying the first year of the adult baccalaureate, specifically the humanities and

social sciences, at an adult education centre in Southern Spain. There is a total of 39.39% men and

60.61% women, with an age range between 18 and 33 years old (M = 23.3; SD = 1.89), where 40.15%

have work, and 35.61% have family responsibilities.

The research was conducted in the first quarter of the 2019–2020 school year. Previously, permission

was requested from both the school management and the students themselves. Both were informed of

the objectives of the research. Neither the school nor the students refused to participate.

3.3. Instrument

The instrument used is an ad hoc questionnaire that has had as reference the questionnaires

77 and 78, which consists of 30 items (Appendix A). These are distributed in different dimensions:

Socioeducational (five items), oriented to know the socio-educational aspects of the sample; motivation

(two items), autonomy (two items); collaboration (two items); participation (two items); resolution

(two items); class time (two items), in which the aim is to identify the attitudes, motivations and

interests of the student in the application of the teaching method; concepts (two items), scientific data

(two items), graphics (two items), results (two items), decision (two items), ratings (three items), which

focus on the learning acquired in the subject of mathematics. In addition, teacher-ratings have been

taken into account, obtaining the values of the grades established by the teacher. The questionnaire

uses a Likert scale, composed of four items (1: None, 2: Few, 3: Enough and 4: Completely).

This questionnaire has been subjected to various statistical tests, for its validation and reliability.

At first, the Delphi method was used, with qualitative validity, by eight experts, whose ratings were

positive (M = 4.66; SD = 0.16; min = 1; max = 6). Then, the statisticians of Kappa de Fleiss and

W de Kendall were used, whose results were adequate (K = 0.89; W = 0.87). Subsequently, it was

validated through exploratory factor analysis with varimax rotation, whose data (Bartlett = 2981.09;

p < 0.001; Kaiser-Meyer-Olkin = 0.89) are adequate. It was finalized using Cronbach’s alpha (0.91),

McDonald’s omega method (0.89), compound reliability (0.85) and mean variance extracted (0.84),

showing adequate metrics. Taking into account the statistical tests, the instrument is considered as

valid and reliable. The internal consistency of each of the dimensions is: Socio-educational (0.941);

motivation (0.884); autonomy (0.861); collaboration (0.952); participation (0.891); resolution (0.948);

class time (0.923); concepts (0.891); scientific data (0.901); graphics (0.912); results (0.884); decision

(0.896); and ratings (0.911).

3.4. Dimensions and Study Variables

The study focuses research on attitudes and mathematical development. Both aspects have

marked the distribution and composition of the dimensions of this study [77,78].

In addition, the dependent and independent variables have been established. The dependent

variables are associated with the dimensions indicated for this study. The teaching method developed

during this research is established as the independent variable. In order to facilitate the understanding

of the results achieved, each of the dimensions is analysed:

• Motivation: Identifies the level of motivation achieved by students in the development of the

teaching and learning process;

• Autonomy: Shows the level of autonomy of the student in the development of the tasks posed;

• Collaboration: Shows the ability to work with other colleagues in the development of the task;

• Participation: It identifies the level of involvement and relationship of the student with the

contents, with the teacher and with his/her fellow students;

• Resolution: It shows the student’s capacity to give an answer to possible problems that may arise

in the performance of class activities;

• Class time: It analyses the feeling of time that the student has in the process of teaching and learning;

The students are studying the first year of the adult baccalaureate, specifically the humanities and

social sciences, at an adult education centre in Southern Spain. There is a total of 39.39% men and

60.61% women, with an age range between 18 and 33 years old (M = 23.3; SD = 1.89), where 40.15%

have work, and 35.61% have family responsibilities.

The research was conducted in the first quarter of the 2019–2020 school year. Previously, permission

was requested from both the school management and the students themselves. Both were informed of

the objectives of the research. Neither the school nor the students refused to participate.

3.3. Instrument

The instrument used is an ad hoc questionnaire that has had as reference the questionnaires

77 and 78, which consists of 30 items (Appendix A). These are distributed in different dimensions:

Socioeducational (five items), oriented to know the socio-educational aspects of the sample; motivation

(two items), autonomy (two items); collaboration (two items); participation (two items); resolution

(two items); class time (two items), in which the aim is to identify the attitudes, motivations and

interests of the student in the application of the teaching method; concepts (two items), scientific data

(two items), graphics (two items), results (two items), decision (two items), ratings (three items), which

focus on the learning acquired in the subject of mathematics. In addition, teacher-ratings have been

taken into account, obtaining the values of the grades established by the teacher. The questionnaire

uses a Likert scale, composed of four items (1: None, 2: Few, 3: Enough and 4: Completely).

This questionnaire has been subjected to various statistical tests, for its validation and reliability.

At first, the Delphi method was used, with qualitative validity, by eight experts, whose ratings were

positive (M = 4.66; SD = 0.16; min = 1; max = 6). Then, the statisticians of Kappa de Fleiss and

W de Kendall were used, whose results were adequate (K = 0.89; W = 0.87). Subsequently, it was

validated through exploratory factor analysis with varimax rotation, whose data (Bartlett = 2981.09;

p < 0.001; Kaiser-Meyer-Olkin = 0.89) are adequate. It was finalized using Cronbach’s alpha (0.91),

McDonald’s omega method (0.89), compound reliability (0.85) and mean variance extracted (0.84),

showing adequate metrics. Taking into account the statistical tests, the instrument is considered as

valid and reliable. The internal consistency of each of the dimensions is: Socio-educational (0.941);

motivation (0.884); autonomy (0.861); collaboration (0.952); participation (0.891); resolution (0.948);

class time (0.923); concepts (0.891); scientific data (0.901); graphics (0.912); results (0.884); decision

(0.896); and ratings (0.911).

3.4. Dimensions and Study Variables

The study focuses research on attitudes and mathematical development. Both aspects have

marked the distribution and composition of the dimensions of this study [77,78].

In addition, the dependent and independent variables have been established. The dependent

variables are associated with the dimensions indicated for this study. The teaching method developed

during this research is established as the independent variable. In order to facilitate the understanding

of the results achieved, each of the dimensions is analysed:

• Motivation: Identifies the level of motivation achieved by students in the development of the

teaching and learning process;

• Autonomy: Shows the level of autonomy of the student in the development of the tasks posed;

• Collaboration: Shows the ability to work with other colleagues in the development of the task;

• Participation: It identifies the level of involvement and relationship of the student with the

contents, with the teacher and with his/her fellow students;

• Resolution: It shows the student’s capacity to give an answer to possible problems that may arise

in the performance of class activities;

• Class time: It analyses the feeling of time that the student has in the process of teaching and learning;

6.
Mathematics 2020, 8, 840 6 of 16

• Concepts: Identifies the level of acquisition, according to the student, of the contents applied in

the pedagogical act;

• Scientific data: Presents the scientific aspects, typical of the mathematics subject, reached by

the students;

• Graphics: It gathers the aspects related to the different mathematical graphs developed during

the formative period;

• Results: It shows the different actions and mathematical problems developed in the realization of

the contents;

• Decisions: Presents the common actions used by the students in order to solve possible activities;

• Ratings: It offers the students’ self-evaluation in the teaching and learning process; and

• Teacher-ratings: Presents the qualification given by the teacher to the students in the pedagogical

act. In this case, the qualification criteria are taken into account.

3.5. Methodological Procedure

The research process developed began with the validation and reliability of the instrument used.

Subsequently, the selection of the sample and the application for permits were made. In this case,

the pedagogical proposal was presented to the selected school, which agreed to participate. The centre,

itself, requested information on the results achieved in the research.

Then, the pedagogical proposals were developed. On the one hand, the traditional exposition

method (Gc), in which the teacher presented the theoretical contents, followed the sequence of the

textbook and proposed tasks. On the other hand, there is the e-learning method (Ge), which will be

explained in more detail in the next point.

At the end of the first quarter, data was collected using Google Form, which is a Google Drive tool.

In other words, the data was collected on the last day of class, in the auditorium of the educational

centre, which has a capacity for 300 people. To do this, the students used their own mobile devices.

In the cases that they did not have, the centre gave them one to fill out the questionnaire. Indicate that

the data collection was carried out at the same time, specifically at 18:10. This data was downloaded in

Excel format and transcribed into the format of the selected statistical program. Finally, the various

statistical tests were carried out and the results obtained were analysed.

3.6. Pedagogic Procedure

The pedagogical proposal developed with the experimental group is based on the e-learning

method. For this purpose, the teacher has made use of the Moodle platform and e-mail. In addition,

every week, a schedule was established, consisting of one hour of group attention and two hours of

individualized attention. The three hours could be developed in a face-to-face way in the educational

centre. It should be noted that these hours were not compulsory. Only those students who considered

it necessary came to the centre, and on a voluntary basis. It should be noted that during the study

procedure, hardly any students attended the centre to answer questions. The group that developed the

expository method, had an hour of tutoring with the teacher of the subject, to solve doubts individually,

or attend to the concerns of the students. During this period, the teacher also attended to the student

through a virtual platform and by e-mail.

The Moodle platform contained all the content to be dealt with in the subject during the first term,

distributed by didactic units. In this case, four didactic units were established for the first quarter.

Each one of the didactic units of the Moodle platform was structured in different sections:

• Theory: Formed by theoretical aspects of the subject, presented in pdf format and explanatory

videos. The intention was to present all the theoretical aspects of the contents to be worked on,

and to reinforce their acquisition through the viewing of videos related to these contents;

• Practice: Composed of activities to show the acquisition of the theoretical contents. These activities

were of introduction, development, consolidation, extension and reinforcement. The activities

• Concepts: Identifies the level of acquisition, according to the student, of the contents applied in

the pedagogical act;

• Scientific data: Presents the scientific aspects, typical of the mathematics subject, reached by

the students;

• Graphics: It gathers the aspects related to the different mathematical graphs developed during

the formative period;

• Results: It shows the different actions and mathematical problems developed in the realization of

the contents;

• Decisions: Presents the common actions used by the students in order to solve possible activities;

• Ratings: It offers the students’ self-evaluation in the teaching and learning process; and

• Teacher-ratings: Presents the qualification given by the teacher to the students in the pedagogical

act. In this case, the qualification criteria are taken into account.

3.5. Methodological Procedure

The research process developed began with the validation and reliability of the instrument used.

Subsequently, the selection of the sample and the application for permits were made. In this case,

the pedagogical proposal was presented to the selected school, which agreed to participate. The centre,

itself, requested information on the results achieved in the research.

Then, the pedagogical proposals were developed. On the one hand, the traditional exposition

method (Gc), in which the teacher presented the theoretical contents, followed the sequence of the

textbook and proposed tasks. On the other hand, there is the e-learning method (Ge), which will be

explained in more detail in the next point.

At the end of the first quarter, data was collected using Google Form, which is a Google Drive tool.

In other words, the data was collected on the last day of class, in the auditorium of the educational

centre, which has a capacity for 300 people. To do this, the students used their own mobile devices.

In the cases that they did not have, the centre gave them one to fill out the questionnaire. Indicate that

the data collection was carried out at the same time, specifically at 18:10. This data was downloaded in

Excel format and transcribed into the format of the selected statistical program. Finally, the various

statistical tests were carried out and the results obtained were analysed.

3.6. Pedagogic Procedure

The pedagogical proposal developed with the experimental group is based on the e-learning

method. For this purpose, the teacher has made use of the Moodle platform and e-mail. In addition,

every week, a schedule was established, consisting of one hour of group attention and two hours of

individualized attention. The three hours could be developed in a face-to-face way in the educational

centre. It should be noted that these hours were not compulsory. Only those students who considered

it necessary came to the centre, and on a voluntary basis. It should be noted that during the study

procedure, hardly any students attended the centre to answer questions. The group that developed the

expository method, had an hour of tutoring with the teacher of the subject, to solve doubts individually,

or attend to the concerns of the students. During this period, the teacher also attended to the student

through a virtual platform and by e-mail.

The Moodle platform contained all the content to be dealt with in the subject during the first term,

distributed by didactic units. In this case, four didactic units were established for the first quarter.

Each one of the didactic units of the Moodle platform was structured in different sections:

• Theory: Formed by theoretical aspects of the subject, presented in pdf format and explanatory

videos. The intention was to present all the theoretical aspects of the contents to be worked on,

and to reinforce their acquisition through the viewing of videos related to these contents;

• Practice: Composed of activities to show the acquisition of the theoretical contents. These activities

were of introduction, development, consolidation, extension and reinforcement. The activities

7.
Mathematics 2020, 8, 840 7 of 16

have been varied, having different types: short answer, long answer, assumptions, problem

solving and autocomplete, relate columns and operations, among others. In this case, all the tools

available in Moodle have been used;

• To know more. In this section students have been allowed to go deeper into the contents of the

subject. This was done through links to web pages on the subject. There were also links to games

related to the contents worked on; and

• Forum: This resource has been used in each didactic unit. The intention was to establish a

debate, both with the teacher and with other colleagues, on the contents dealt with in the subject.

In addition, it has served to resolve doubts and pose small riddles related to the aspects worked on.

The evaluation methods and instruments used have been:

• Written test (50% of the quarterly mark): This test was taken at the end of the quarter. The types

of questions were short answer and long answer; and

• Systematic observation (50% of the quarterly mark): Participation in the forum and the

development of the activities set out in the Moodle platform were analysed. The instrument used

was a heading.

On the other hand, the pedagogical proposal developed by the control group was based on

the presentation of theoretical contents by the teacher. In addition, activities have been developed,

both from the textbook and from cards given by the teacher. As a method and instrument of evaluation,

the following have been applied:

• Written test (50% of the quarterly mark): This test was taken at the end of the quarter. The question

type was short answer and long answer; and

• Systematic observation (50% of the quarterly mark): The development and elaboration of the

activities proposed by the teacher were analysed. The instrument used was a heading.

4. Results

The data presented in Table 2, after the descriptive statistical analysis, show diversity of response

among students who attend both the night school and the distance school. According to the data

provided by the asymmetry and kurtosis statisticians, the response distribution is considered normal.

This is because the values are between ±1.96, according to [79]. The students in the control group show

a mean response that is around 2. Some dimensions are slightly below and others are slightly above.

In the control group the dimension with the highest rating is resolution. In contrast, the dimension

with the lowest rating is decision. The students in the experimental group show a response tendency

that is around 2.5 points. The least valued dimension in the experimental group is decision. The most

valued dimension in the experimental group is teacher-ratings. According to the statistic that shows

the standard deviation, an even trend of response is observed in the students. This is presented in

all the dimensions of the study, both in the control group and in the experimental group. Kurtosis is

platykurtic in all study dimensions, both in the control group and in the experimental group.

have been varied, having different types: short answer, long answer, assumptions, problem

solving and autocomplete, relate columns and operations, among others. In this case, all the tools

available in Moodle have been used;

• To know more. In this section students have been allowed to go deeper into the contents of the

subject. This was done through links to web pages on the subject. There were also links to games

related to the contents worked on; and

• Forum: This resource has been used in each didactic unit. The intention was to establish a

debate, both with the teacher and with other colleagues, on the contents dealt with in the subject.

In addition, it has served to resolve doubts and pose small riddles related to the aspects worked on.

The evaluation methods and instruments used have been:

• Written test (50% of the quarterly mark): This test was taken at the end of the quarter. The types

of questions were short answer and long answer; and

• Systematic observation (50% of the quarterly mark): Participation in the forum and the

development of the activities set out in the Moodle platform were analysed. The instrument used

was a heading.

On the other hand, the pedagogical proposal developed by the control group was based on

the presentation of theoretical contents by the teacher. In addition, activities have been developed,

both from the textbook and from cards given by the teacher. As a method and instrument of evaluation,

the following have been applied:

• Written test (50% of the quarterly mark): This test was taken at the end of the quarter. The question

type was short answer and long answer; and

• Systematic observation (50% of the quarterly mark): The development and elaboration of the

activities proposed by the teacher were analysed. The instrument used was a heading.

4. Results

The data presented in Table 2, after the descriptive statistical analysis, show diversity of response

among students who attend both the night school and the distance school. According to the data

provided by the asymmetry and kurtosis statisticians, the response distribution is considered normal.

This is because the values are between ±1.96, according to [79]. The students in the control group show

a mean response that is around 2. Some dimensions are slightly below and others are slightly above.

In the control group the dimension with the highest rating is resolution. In contrast, the dimension

with the lowest rating is decision. The students in the experimental group show a response tendency

that is around 2.5 points. The least valued dimension in the experimental group is decision. The most

valued dimension in the experimental group is teacher-ratings. According to the statistic that shows

the standard deviation, an even trend of response is observed in the students. This is presented in

all the dimensions of the study, both in the control group and in the experimental group. Kurtosis is

platykurtic in all study dimensions, both in the control group and in the experimental group.

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Mathematics 2020, 8, 840 8 of 16

Table 2. Results obtained for the dimensions of study in GC and EG of high school students.

Likert Scale n (%) Parameters

Dimensions None Few Enough Completely M SD Skw Kme

Motivation 24(39.3) 19(31.1) 14(23) 4(6.6) 1.97 0.948 0.552 −0.757

Autonomy 26(42.6) 17(27.9) 13(21.3) 5(8.2) 1.95 0.990 0.633 −0.760

Collaboration 20(32.8) 19(31.1) 16(26.2) 6(9.8) 2.13 0.991 0.366 −0.961

Participation 23(37.7) 22(36.1) 13(21.3) 3(4.9) 1.93 0.892 0.568 −0.569

Control group

Resolution 13(21.3) 16(26.2) 24(39.3) 8(13.1) 2.44 0.975 −0.112 −0.990

Class time 23(37.7) 19(31.1) 13(21.3) 6(9.8) 2.03 0.999 0.554 −0.804

Concepts 21(34.4) 19(31.1) 15(24.6) 6(9.8) 2.10 0.995 0.427 −0.921

Scientific data 26(42.6) 18(29.5) 13(21.3) 4(6.6) 1.92 0.954 0.644 −0.676

Graphics 24(39.3) 18(29.5) 15(24.6) 4(6.6) 1.98 0.957 0.505 −0.862

Results 18(29.5) 23(37.7) 13(21.3) 7(11.5) 2.15 0.980 0.462 −0.753

Decision 28(45.9) 17(27.9) 14(23) 2(3.3) 1.84 0.898 0.620 −0.796

Ratings a 21(34.4) 19(31.1) 16(26.2) 5(8.2) 2.08 0.971 0.396 −0.924

Teacher ratings a 12(19.7) 23(37.7) 17(27.9) 9(14.8) 2.38 0.969 0.190 −0.886

Motivation 6(8.5) 20(28.2) 24(33.8) 21(29.6) 2.85 0.951 −0.296 −0.904

Autonomy 8(11.3) 11(15.5) 27(38) 25(35.2) 2.97 0.985 −0.680 −0.551

Collaboration 18(25.4) 24(33.8) 21(29.6) 8(11.3) 2.27 0.970 0.205 −0.994

Experimental group

Participation 7(9.9) 16(22.5) 25(35.2) 23(32.4) 2.90 0.973 −0.467 −0.782

Resolution 9(12.7) 19(26.8) 24(33.8) 19(26.8) 2.75 0.996 −0.268 −0.972

Class time 15(21.1) 32(45.1) 12(16.9) 12(16.9) 2.30 0.991 0.455 −0.768

Concepts 7(9.9) 16(22.5) 24(33.8) 24(33.8) 2.92 0.982 −0.479 −0.881

Scientific data 18(25.4) 27(38) 16(22.5) 10(14.1) 2.25 0.996 0.358 −0.878

Graphics 16(22.5) 29(40.8) 15(21.1) 11(15.5) 2.30 0.991 0.364 −0.847

Results 5(7) 19(26.8) 21(29.6) 26(36.6) 2.96 0.963 −0.408 −0.956

Decision 24(33.8) 26(36.6) 13(18.3) 8(11.3) 2.07 0.990 0.582 −0.671

Ratings a 7(9.9) 16(22.5) 23(32.4) 25(35.2) 2.93 0.990 −0.492 −0.838

Teacher ratings a 5(7) 16(22.5) 23(32.4) 27(38) 3.01 0.949 −0.545 −0.736

a. Established grade group (None: 1–4.9; Few: 5–5.9; Enough: 6–8.9; Completely: 9–10).

The means presented by the control group and the experimental group show relevant differences.

In the control group, there is diversity of means between the study dimensions. The resolution and

teacher-ratings dimensions stand out from the total mean. On the other hand, the decision dimension is

much lower than the mean. In the experimental group, these differences are more pressing. In this case,

the dimensions motivation, autonomy, participation, resolution, concepts, results, ratings and teacher

ratings are located above the mean. On the other hand, the collaboration, class time, scientific-data,

graphics and decision dimensions are located far below the totalised mean. Furthermore, even ratings

are observed, both in the control group and in the experimental group, in the collaboration, class time,

scientific-data, graphics and decision dimensions (Figure 1).

To identify the value of independence between the expository-traditional method and the

e-learning method, Student’s t statistical test has been used. The values present higher averages in

favour of the experimental group, although it is not significant in all cases. The dimensions motivation,

autonomy, participation, concepts, results, ratings and teacher-ratings show a significant relationship.

In all the dimensions where there is a relationship of significance, the force of association is average,

if the values of the biserial correlation are taken into account. The size of the effect is low in class time

and graphics, and very low in the rest of the dimensions (Table 3).

Table 2. Results obtained for the dimensions of study in GC and EG of high school students.

Likert Scale n (%) Parameters

Dimensions None Few Enough Completely M SD Skw Kme

Motivation 24(39.3) 19(31.1) 14(23) 4(6.6) 1.97 0.948 0.552 −0.757

Autonomy 26(42.6) 17(27.9) 13(21.3) 5(8.2) 1.95 0.990 0.633 −0.760

Collaboration 20(32.8) 19(31.1) 16(26.2) 6(9.8) 2.13 0.991 0.366 −0.961

Participation 23(37.7) 22(36.1) 13(21.3) 3(4.9) 1.93 0.892 0.568 −0.569

Control group

Resolution 13(21.3) 16(26.2) 24(39.3) 8(13.1) 2.44 0.975 −0.112 −0.990

Class time 23(37.7) 19(31.1) 13(21.3) 6(9.8) 2.03 0.999 0.554 −0.804

Concepts 21(34.4) 19(31.1) 15(24.6) 6(9.8) 2.10 0.995 0.427 −0.921

Scientific data 26(42.6) 18(29.5) 13(21.3) 4(6.6) 1.92 0.954 0.644 −0.676

Graphics 24(39.3) 18(29.5) 15(24.6) 4(6.6) 1.98 0.957 0.505 −0.862

Results 18(29.5) 23(37.7) 13(21.3) 7(11.5) 2.15 0.980 0.462 −0.753

Decision 28(45.9) 17(27.9) 14(23) 2(3.3) 1.84 0.898 0.620 −0.796

Ratings a 21(34.4) 19(31.1) 16(26.2) 5(8.2) 2.08 0.971 0.396 −0.924

Teacher ratings a 12(19.7) 23(37.7) 17(27.9) 9(14.8) 2.38 0.969 0.190 −0.886

Motivation 6(8.5) 20(28.2) 24(33.8) 21(29.6) 2.85 0.951 −0.296 −0.904

Autonomy 8(11.3) 11(15.5) 27(38) 25(35.2) 2.97 0.985 −0.680 −0.551

Collaboration 18(25.4) 24(33.8) 21(29.6) 8(11.3) 2.27 0.970 0.205 −0.994

Experimental group

Participation 7(9.9) 16(22.5) 25(35.2) 23(32.4) 2.90 0.973 −0.467 −0.782

Resolution 9(12.7) 19(26.8) 24(33.8) 19(26.8) 2.75 0.996 −0.268 −0.972

Class time 15(21.1) 32(45.1) 12(16.9) 12(16.9) 2.30 0.991 0.455 −0.768

Concepts 7(9.9) 16(22.5) 24(33.8) 24(33.8) 2.92 0.982 −0.479 −0.881

Scientific data 18(25.4) 27(38) 16(22.5) 10(14.1) 2.25 0.996 0.358 −0.878

Graphics 16(22.5) 29(40.8) 15(21.1) 11(15.5) 2.30 0.991 0.364 −0.847

Results 5(7) 19(26.8) 21(29.6) 26(36.6) 2.96 0.963 −0.408 −0.956

Decision 24(33.8) 26(36.6) 13(18.3) 8(11.3) 2.07 0.990 0.582 −0.671

Ratings a 7(9.9) 16(22.5) 23(32.4) 25(35.2) 2.93 0.990 −0.492 −0.838

Teacher ratings a 5(7) 16(22.5) 23(32.4) 27(38) 3.01 0.949 −0.545 −0.736

a. Established grade group (None: 1–4.9; Few: 5–5.9; Enough: 6–8.9; Completely: 9–10).

The means presented by the control group and the experimental group show relevant differences.

In the control group, there is diversity of means between the study dimensions. The resolution and

teacher-ratings dimensions stand out from the total mean. On the other hand, the decision dimension is

much lower than the mean. In the experimental group, these differences are more pressing. In this case,

the dimensions motivation, autonomy, participation, resolution, concepts, results, ratings and teacher

ratings are located above the mean. On the other hand, the collaboration, class time, scientific-data,

graphics and decision dimensions are located far below the totalised mean. Furthermore, even ratings

are observed, both in the control group and in the experimental group, in the collaboration, class time,

scientific-data, graphics and decision dimensions (Figure 1).

To identify the value of independence between the expository-traditional method and the

e-learning method, Student’s t statistical test has been used. The values present higher averages in

favour of the experimental group, although it is not significant in all cases. The dimensions motivation,

autonomy, participation, concepts, results, ratings and teacher-ratings show a significant relationship.

In all the dimensions where there is a relationship of significance, the force of association is average,

if the values of the biserial correlation are taken into account. The size of the effect is low in class time

and graphics, and very low in the rest of the dimensions (Table 3).

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Mathematics 2020, 8, 840 9 of 16

Figure 1. Comparison between control group and experimental group.

Table 3. Study of the value of independence between control group and experimental group.

Dimensions µ(X1−X2) tn1+n2−2 df d rxy

Motivation −0.878 (1.97−2.85) −5.295 ** 130 0.094 0.421

Autonomy −1.021 (1.95−2.97) −5.922 ** 130 0.062 0.461

Collaboration −0.136 (2.13−2.27) −0.798 130 0.036 0.070

Participation −0.967 (1.93−2.90) −5.914 ** 130 0.048 0.460

Resolution −0.304 (2.44−2.75) −1.765 130 0.029 0.153

Class time −0.263 (2.03−2.30) −1.514 130 0.115 0.132

Concepts −0.817 (2.10−2.92) −4.737 ** 130 0.052 0.384

Scientific data −0.335 (1.92−2.25) −1.967 130 0.097 0.170

Graphics −0.312 (1.98−2.30) −1.833 130 0.105 0.159

Results −0.810 (2.15−2.96) −4.780 ** 130 0.038 0.387

Decision −0.234 (1.84−2.07) −1.415 130 0.081 0.123

Ratings a −0.848 (2.08-2.93) −4.947 ** 130 0.052 0.398

Teacher ratings a −0.637 (2.38−3.01) −3.809 ** 130 −0.008 0.317

**. The correlation is significant at the level 0.01. a . Established grade group (None: 1–4.9; Few: 5–5.9; Enough:

6–8.9; Completely: 9–10).

5. Discussion

The rise of information and communication technologies, related to the current situation of

confinement caused by COVID-19, makes the e-learning method relevant in recent times, thus

promoting innovative educational practices [1–6].

The e-learning teaching method breaks with the classic stereotypes of teaching and learning

processes, since it modifies the spaces and time of training, allowing the development of the pedagogical

act in any place and at any time. This can be achieved if technological devices and digital resources are

available, as well as internet access [22–27].

In the present research, the influence of e-learning in the field of mathematics has been analysed,

in contrast to the traditional expository method, in adult students who are studying for high school.

As shown in the results obtained, there are significant differences between the values achieved in

the control group and the experimental group. These differences have always been in favour of the

e-learning method.

In the group where the expository method has been developed, the lowest values have been

produced in the decision. In this case, students have difficulties in making decisions by themselves

Figure 1. Comparison between control group and experimental group.

Table 3. Study of the value of independence between control group and experimental group.

Dimensions µ(X1−X2) tn1+n2−2 df d rxy

Motivation −0.878 (1.97−2.85) −5.295 ** 130 0.094 0.421

Autonomy −1.021 (1.95−2.97) −5.922 ** 130 0.062 0.461

Collaboration −0.136 (2.13−2.27) −0.798 130 0.036 0.070

Participation −0.967 (1.93−2.90) −5.914 ** 130 0.048 0.460

Resolution −0.304 (2.44−2.75) −1.765 130 0.029 0.153

Class time −0.263 (2.03−2.30) −1.514 130 0.115 0.132

Concepts −0.817 (2.10−2.92) −4.737 ** 130 0.052 0.384

Scientific data −0.335 (1.92−2.25) −1.967 130 0.097 0.170

Graphics −0.312 (1.98−2.30) −1.833 130 0.105 0.159

Results −0.810 (2.15−2.96) −4.780 ** 130 0.038 0.387

Decision −0.234 (1.84−2.07) −1.415 130 0.081 0.123

Ratings a −0.848 (2.08-2.93) −4.947 ** 130 0.052 0.398

Teacher ratings a −0.637 (2.38−3.01) −3.809 ** 130 −0.008 0.317

**. The correlation is significant at the level 0.01. a . Established grade group (None: 1–4.9; Few: 5–5.9; Enough:

6–8.9; Completely: 9–10).

5. Discussion

The rise of information and communication technologies, related to the current situation of

confinement caused by COVID-19, makes the e-learning method relevant in recent times, thus

promoting innovative educational practices [1–6].

The e-learning teaching method breaks with the classic stereotypes of teaching and learning

processes, since it modifies the spaces and time of training, allowing the development of the pedagogical

act in any place and at any time. This can be achieved if technological devices and digital resources are

available, as well as internet access [22–27].

In the present research, the influence of e-learning in the field of mathematics has been analysed,

in contrast to the traditional expository method, in adult students who are studying for high school.

As shown in the results obtained, there are significant differences between the values achieved in

the control group and the experimental group. These differences have always been in favour of the

e-learning method.

In the group where the expository method has been developed, the lowest values have been

produced in the decision. In this case, students have difficulties in making decisions by themselves

10.
Mathematics 2020, 8, 840 10 of 16

when solving the proposed mathematical problems. On the other hand, the most valued dimension is

the resolution, that is, the carrying out of activities in class. This may be due to the fact that the teacher,

present in the expository method, can respond to the needs that the students may have during the

development of the different practices.

In the group where the e-learning method is developed the dimension with the highest score is

teacher-rating. This shows that the students’ grades are increasing, being in line with [58]. On the

other hand, the less valued dimension, as in the control group, is decision. In other words, neither

the expository-traditional method nor the e-learning method allows the student’s decision-making to

improve when it comes to solving a problem on their own.

Both in the control group and in the experimental group, students have shown a tendency to

respond evenly. This shows that the students agree on the teaching methods applied. This does

not mean that there are equal values in all the study dimensions. In the control group the means of

the dimensions have not been equal to each other. Examples of this are the dimensions resolution

and teacher-ratings, which are above the totalised mean. That is to say, for the students who have

developed the expository method, in these dimensions, they show a better evaluation. On the other

hand, the decision dimension is much lower than the average.

Something similar occurs in the experimental group. The averages thrown between the different

dimensions are not equal to each other. In this case, the contrasts are more relevant. For example,

the dimensions motivation, autonomy, participation, resolution, concepts, results, ratings and teacher

ratings are above the total average. On the other hand, the collaboration, class time, scientific-data,

graphics and decision dimensions are much lower than the total average.

If the means of the control group and the experimental group are compared, there are dimensions in

which there are no significant differences. This is the case of the collaboration, class time, scientific-data,

graphics and decision dimensions, which present evenly distributed means, although always with

higher values in the experimental group.

Where there are significant differences, in favour of the e-learning method, are in the dimensions

of motivation [36,59], autonomy [35], participation [60], concepts [55], results, ratings and teacher

ratings [58]. In other words, the e-learning method favours these aspects in the pedagogical act.

In the dimension where there is a greater contrast, when comparing the expository-traditional

method with the e-learning method, it is in autonomy. This may be mainly due to the fact that the

e-learning method favours self-regulation of learning [39].

If this study is compared with other studies in which e-learning has been developed, improvements

in students can be observed. On the one hand, there is an improvement in motivation, autonomy,

participation, concepts, results and grades. All these aspects are reflected in other studies, in which the

e-learning method is associated with a clearly defined and structured pedagogical approach. In the

studies analysed, student effort, which has an impact on their qualifications, is due to increased

motivation and interest. In other words, the pedagogical approach influences whether the student

can be more or less motivated. In addition, the fact that the student is more motivated leads to an

increase in participation, which will lead to improvements in the acquisition of mathematical concepts.

It will also influence the resolution of various activities. All of this is ultimately reflected in the grades,

which increase. Therefore, it can be indicated that there is an improvement in students’ academic

performance. Furthermore, it should be taken into account that the e-learning method will favour the

autonomy of the student, adapting to his or her learning style, which implies more individualised

attention to the teaching and learning process. What is clear from all this research is that the e-learning

method is associated with a clearly defined pedagogical process, as shown in this research [64–70].

6. Conclusions

In general, it can be indicated that the dimensions of motivation, autonomy, participation, concepts,

results, self-evaluation and teacher qualification have proved to be significant. That is to say, according

to the study group, differences are observed in the evaluations given by the students. It should be

when solving the proposed mathematical problems. On the other hand, the most valued dimension is

the resolution, that is, the carrying out of activities in class. This may be due to the fact that the teacher,

present in the expository method, can respond to the needs that the students may have during the

development of the different practices.

In the group where the e-learning method is developed the dimension with the highest score is

teacher-rating. This shows that the students’ grades are increasing, being in line with [58]. On the

other hand, the less valued dimension, as in the control group, is decision. In other words, neither

the expository-traditional method nor the e-learning method allows the student’s decision-making to

improve when it comes to solving a problem on their own.

Both in the control group and in the experimental group, students have shown a tendency to

respond evenly. This shows that the students agree on the teaching methods applied. This does

not mean that there are equal values in all the study dimensions. In the control group the means of

the dimensions have not been equal to each other. Examples of this are the dimensions resolution

and teacher-ratings, which are above the totalised mean. That is to say, for the students who have

developed the expository method, in these dimensions, they show a better evaluation. On the other

hand, the decision dimension is much lower than the average.

Something similar occurs in the experimental group. The averages thrown between the different

dimensions are not equal to each other. In this case, the contrasts are more relevant. For example,

the dimensions motivation, autonomy, participation, resolution, concepts, results, ratings and teacher

ratings are above the total average. On the other hand, the collaboration, class time, scientific-data,

graphics and decision dimensions are much lower than the total average.

If the means of the control group and the experimental group are compared, there are dimensions in

which there are no significant differences. This is the case of the collaboration, class time, scientific-data,

graphics and decision dimensions, which present evenly distributed means, although always with

higher values in the experimental group.

Where there are significant differences, in favour of the e-learning method, are in the dimensions

of motivation [36,59], autonomy [35], participation [60], concepts [55], results, ratings and teacher

ratings [58]. In other words, the e-learning method favours these aspects in the pedagogical act.

In the dimension where there is a greater contrast, when comparing the expository-traditional

method with the e-learning method, it is in autonomy. This may be mainly due to the fact that the

e-learning method favours self-regulation of learning [39].

If this study is compared with other studies in which e-learning has been developed, improvements

in students can be observed. On the one hand, there is an improvement in motivation, autonomy,

participation, concepts, results and grades. All these aspects are reflected in other studies, in which the

e-learning method is associated with a clearly defined and structured pedagogical approach. In the

studies analysed, student effort, which has an impact on their qualifications, is due to increased

motivation and interest. In other words, the pedagogical approach influences whether the student

can be more or less motivated. In addition, the fact that the student is more motivated leads to an

increase in participation, which will lead to improvements in the acquisition of mathematical concepts.

It will also influence the resolution of various activities. All of this is ultimately reflected in the grades,

which increase. Therefore, it can be indicated that there is an improvement in students’ academic

performance. Furthermore, it should be taken into account that the e-learning method will favour the

autonomy of the student, adapting to his or her learning style, which implies more individualised

attention to the teaching and learning process. What is clear from all this research is that the e-learning

method is associated with a clearly defined pedagogical process, as shown in this research [64–70].

6. Conclusions

In general, it can be indicated that the dimensions of motivation, autonomy, participation, concepts,

results, self-evaluation and teacher qualification have proved to be significant. That is to say, according

to the study group, differences are observed in the evaluations given by the students. It should be

11.
Mathematics 2020, 8, 840 11 of 16

borne in mind that these differences may be motivated by the application of the teaching method

applied. In one group the expository method has been developed and in the other the e-learning

method. The most valued dimensions have been those of the group in which the e-learning method

has been developed. This can be due to several reasons. One of them is the applied method, since

the e-learning method makes the student the guide of his/her own learning. That is, they have more

weight in the teaching and learning process, while the teacher is a guide. This aspect can have a direct

influence on motivation, autonomy and participation. This fact, in turn, can lead to a better acquisition

of mathematical concepts and results, given that being motivated and having more autonomy in

learning, allows the student to increase his or her participation, and in his or her view, to present

more interest in the contents being developed. Finally, the improvement in the concepts and results

generates an improvement in the qualification of the students, and therefore, an improvement in the

self-evaluation of the didactic actions developed. The rest of the dimensions, such as collaboration,

resolution, class time, scientific data, graphics and decision, no differences were observed. This may

be due to the method itself. In this case, both the e-learning method and the expository method, due

to their didactic processes, do not require greater collaboration among students, nor in the feeling of

class time. The other dimensions may be due to the fact that neither the expository method nor the

e-learning method lead to an increase in the understanding and development of scientific data, the

development of graphs or decision-making.

It can be concluded that the e-learning method is an improvement for adult students who are

studying mathematics in the educational stage of high school, provided that it is compared with the

expository method. In this case, the improvements occur in motivation, autonomy, participation,

concepts, results, ratings and teacher-ratings. Therefore, the use of the e-learning method would be

effective for its implementation with adults who study mathematics in high school.

The prospective of the research is based on two aspects. On the one hand, the aim is to present the

scientific community with new data on the application of innovative teaching methods. In this case,

the e-learning method is compared with the traditional expository method for teaching mathematics

to adults studying in secondary schools. On the other hand, the aim is to publicise the educational

practice developed in this research, so that other teachers, in similar circumstances, can develop it.

The limitations of the study are several. On the one hand, the study sample presents some

specific socio-educational characteristics, so one must be cautious when extrapolating the data to other

populations. The access to the sample has been for convenience, due to the fact that the educational

groups are established by the educational centres themselves. This has prevented the application

of other sampling techniques. Finally, the fact of not applying a pretest and posttest study process

makes it impossible to be categorical in ensuring that the e-learning method directly influences the

dimensions, since there may be other elements that may have been include in the development of the

study. Therefore, the results obtained should be treated with caution.

As a future line of research, it is presented to develop this didactic method in other educational

stages and in other educational subjects.

Author Contributions: Conceptualization: I.A.-D. and P.C.-R.; methodology: P.C.-R.; software: A.-.J.M.-G.; formal

analysis: A.-J.M.-G.; investigation: I.A.-D., P.C.-R., A.-J.M.-G. and S.A.-G.; data curation: P.C.-R. and A.-J.M.-G.;

writing—original draft preparation: I.A.-D., P.C.-R., A.-J.M.-G. and S.A.-G.; writing—review and editing: I.A.-D.,

P.C.-R., A.-J.M.-G. and S.A.-G.; visualization: I.A.-D.; supervision: S.A.-G. All authors have read and agreed to the

published version of the manuscript.

Funding: This study has been financed by the “Study and analysis of technological resources and innovation in

teacher training in the field of Higher Education and its applicability to the development of the Santander Region

(Colombia)”, in the Framework Cooperation Agreement for the strengthening of research and education, signed

between the Corporación Escuela Tecnológica del Oriente, the Secretariat of Education of Santander and the AreA

HUM/672 Research Group of the University of Granada. Code: ISPRS-2017-7202. Period: 2017–2021.

Acknowledgments: We acknowledge the researchers of the research group AREA (HUM-672), which belongs to

the Ministry of Education and Science of the Junta de Andalucía and is registered in the Department of Didactics

and School Organization of the Faculty of Education Sciences of the University of Granada.

Conflicts of Interest: The authors declare no conflict of interest.

borne in mind that these differences may be motivated by the application of the teaching method

applied. In one group the expository method has been developed and in the other the e-learning

method. The most valued dimensions have been those of the group in which the e-learning method

has been developed. This can be due to several reasons. One of them is the applied method, since

the e-learning method makes the student the guide of his/her own learning. That is, they have more

weight in the teaching and learning process, while the teacher is a guide. This aspect can have a direct

influence on motivation, autonomy and participation. This fact, in turn, can lead to a better acquisition

of mathematical concepts and results, given that being motivated and having more autonomy in

learning, allows the student to increase his or her participation, and in his or her view, to present

more interest in the contents being developed. Finally, the improvement in the concepts and results

generates an improvement in the qualification of the students, and therefore, an improvement in the

self-evaluation of the didactic actions developed. The rest of the dimensions, such as collaboration,

resolution, class time, scientific data, graphics and decision, no differences were observed. This may

be due to the method itself. In this case, both the e-learning method and the expository method, due

to their didactic processes, do not require greater collaboration among students, nor in the feeling of

class time. The other dimensions may be due to the fact that neither the expository method nor the

e-learning method lead to an increase in the understanding and development of scientific data, the

development of graphs or decision-making.

It can be concluded that the e-learning method is an improvement for adult students who are

studying mathematics in the educational stage of high school, provided that it is compared with the

expository method. In this case, the improvements occur in motivation, autonomy, participation,

concepts, results, ratings and teacher-ratings. Therefore, the use of the e-learning method would be

effective for its implementation with adults who study mathematics in high school.

The prospective of the research is based on two aspects. On the one hand, the aim is to present the

scientific community with new data on the application of innovative teaching methods. In this case,

the e-learning method is compared with the traditional expository method for teaching mathematics

to adults studying in secondary schools. On the other hand, the aim is to publicise the educational

practice developed in this research, so that other teachers, in similar circumstances, can develop it.

The limitations of the study are several. On the one hand, the study sample presents some

specific socio-educational characteristics, so one must be cautious when extrapolating the data to other

populations. The access to the sample has been for convenience, due to the fact that the educational

groups are established by the educational centres themselves. This has prevented the application

of other sampling techniques. Finally, the fact of not applying a pretest and posttest study process

makes it impossible to be categorical in ensuring that the e-learning method directly influences the

dimensions, since there may be other elements that may have been include in the development of the

study. Therefore, the results obtained should be treated with caution.

As a future line of research, it is presented to develop this didactic method in other educational

stages and in other educational subjects.

Author Contributions: Conceptualization: I.A.-D. and P.C.-R.; methodology: P.C.-R.; software: A.-.J.M.-G.; formal

analysis: A.-J.M.-G.; investigation: I.A.-D., P.C.-R., A.-J.M.-G. and S.A.-G.; data curation: P.C.-R. and A.-J.M.-G.;

writing—original draft preparation: I.A.-D., P.C.-R., A.-J.M.-G. and S.A.-G.; writing—review and editing: I.A.-D.,

P.C.-R., A.-J.M.-G. and S.A.-G.; visualization: I.A.-D.; supervision: S.A.-G. All authors have read and agreed to the

published version of the manuscript.

Funding: This study has been financed by the “Study and analysis of technological resources and innovation in

teacher training in the field of Higher Education and its applicability to the development of the Santander Region

(Colombia)”, in the Framework Cooperation Agreement for the strengthening of research and education, signed

between the Corporación Escuela Tecnológica del Oriente, the Secretariat of Education of Santander and the AreA

HUM/672 Research Group of the University of Granada. Code: ISPRS-2017-7202. Period: 2017–2021.

Acknowledgments: We acknowledge the researchers of the research group AREA (HUM-672), which belongs to

the Ministry of Education and Science of the Junta de Andalucía and is registered in the Department of Didactics

and School Organization of the Faculty of Education Sciences of the University of Granada.

Conflicts of Interest: The authors declare no conflict of interest.

12.
Mathematics 2020, 8, 840 12 of 16

Appendix A

Table A1. The instrument used is an ad hoc questionnaire.

Socio-Educational Dimension

Variable Item Choice

Man

Gender Gender

Woman

18–19 years

20–21 years

Age Age

22–23 years

24 or more years

Christian

Muslim

Jewish

Religion Religion

Hindu

Atheist

Other

From 0 to 2 h a day

ICT use

How much time do you spend using ICTs every day? From 2 to 4 h a day

frequency

More than 4 h a day

Low Level

Context What is your socioeconomic level? Medium level

High level

Gradation

Dimensions Variable

1 2 3 4

Does the methodology applied affect your motivation with regard to

Motivation

mathematical content?

To what extent has the methodology applied improved your

motivation with regard to mathematical content?

How does the methodology applied in the field of mathematics

Autonomy

contribute to their autonomy?

To what extent has the methodology applied in the field of mathematics

contributed to their autonomy?

How does the methodology developed in the subject of mathematics

Collaboration

affect the collaboration of the group?

To what extent has the methodology applied in the subject of

mathematics contributed to the collaboration of group’s collaboration?

How has the methodology applied in the field of mathematics

Participation

contributed to their level of participation?

Has the methodology applied to their level of involvement in the

subject of mathematics increased?

How does the methodology developed in the field of mathematics

Resolution

affect the resolution of problems that arise during the study?

To what extent does the methodology applied in the subject of

mathematics contribute to your ability to solve the problems that arise

during the study?

How does the methodology developed in the field of mathematics

Class-time

affect the feeling of class time?

Do you feel that time passes more quickly in math with the

methodology applied?

How does the methodology developed in the subject of mathematics to

Concepts

learning scientific language and mathematical concepts?

To what extent has the methodology applied in the field of mathematics

contributed to your knowledge of scientific language and

mathematical concepts?

How does methodology applied in the subject of mathematics affect the

Scientific data

use of scientific data and processes?

To what extent has the methodology applied in the subject of

mathematics contributed to the use of data and scientific processes?

Appendix A

Table A1. The instrument used is an ad hoc questionnaire.

Socio-Educational Dimension

Variable Item Choice

Man

Gender Gender

Woman

18–19 years

20–21 years

Age Age

22–23 years

24 or more years

Christian

Muslim

Jewish

Religion Religion

Hindu

Atheist

Other

From 0 to 2 h a day

ICT use

How much time do you spend using ICTs every day? From 2 to 4 h a day

frequency

More than 4 h a day

Low Level

Context What is your socioeconomic level? Medium level

High level

Gradation

Dimensions Variable

1 2 3 4

Does the methodology applied affect your motivation with regard to

Motivation

mathematical content?

To what extent has the methodology applied improved your

motivation with regard to mathematical content?

How does the methodology applied in the field of mathematics

Autonomy

contribute to their autonomy?

To what extent has the methodology applied in the field of mathematics

contributed to their autonomy?

How does the methodology developed in the subject of mathematics

Collaboration

affect the collaboration of the group?

To what extent has the methodology applied in the subject of

mathematics contributed to the collaboration of group’s collaboration?

How has the methodology applied in the field of mathematics

Participation

contributed to their level of participation?

Has the methodology applied to their level of involvement in the

subject of mathematics increased?

How does the methodology developed in the field of mathematics

Resolution

affect the resolution of problems that arise during the study?

To what extent does the methodology applied in the subject of

mathematics contribute to your ability to solve the problems that arise

during the study?

How does the methodology developed in the field of mathematics

Class-time

affect the feeling of class time?

Do you feel that time passes more quickly in math with the

methodology applied?

How does the methodology developed in the subject of mathematics to

Concepts

learning scientific language and mathematical concepts?

To what extent has the methodology applied in the field of mathematics

contributed to your knowledge of scientific language and

mathematical concepts?

How does methodology applied in the subject of mathematics affect the

Scientific data

use of scientific data and processes?

To what extent has the methodology applied in the subject of

mathematics contributed to the use of data and scientific processes?

13.
Mathematics 2020, 8, 840 13 of 16

Table A1. Cont.

Socio-Educational Dimension

How does the methodology applied in the subject of mathematics affect

Graphics

the ability to analyse and represent graphs?

How much has the methodology applied in the subject of mathematics

contributed to your ability to analyse and represent graphs?

How does the methodology applied in the subject of mathematics affect

Results

the ability to interpret and reflect the results of the proposed activities?

To what extent has the methodology applied in the subject of

mathematics contributed to your ability to interpret and reflect the

results of the proposed activities?

How does the methodology applied in the subject of mathematics to

Decision

the development of mathematical competence?

To what extent has the methodology applied in the subject of

mathematics contributed to your ability to make decisions?

0–4.9

5–5.9

What is your average grade in general?

6–8.9

9–10

0–4.9

5–5.9

Ratings What is your general average in the Mathematics subject?

6–8.9

9–10

0–4.9

What has been the grade you have obtained in the Mathematics subject after 5–5.9

the development of the experience? 6–8.9

9–10

1. Alonso-García, S.; Aznar-Díaz, I.; Cáceres-Reche, M.P.; Trujillo-Torres, J.M.; Romero-Rodríguez, J.M.

Systematic Review of Good Teaching Practices with ICT in Spanish Higher Education. Trends and

Challenges for Sustainability. Sustainability 2019, 11, 7150. [CrossRef]

2. Hinojo, F.J.; Aznar, I.; Romero, J.M.; Marín, J.A. Influencia del aula invertida en el rendimiento académico.

Una revisión sistemática. Campus Virtuales 2019, 8, 9–18.

3. Hinojo, F.J.; Mingorance, A.C.; Trujillo, J.M.; Aznar, I.; Cáceres, M.P. Incidence of the flipped classroom in

the physical education students’ academic performance in university contexts. Sustainability 2018, 10, 1334.

[CrossRef]

4. Maldonado, G.A.; García, J.; Sampedro-Requena, B. The effect of ICT and social networks on university

students. RIED 2019, 22, 153–176. [CrossRef]

5. Area, M.; Hernández, V.; Sosa, J.J. Modelos de integración didáctica de las TIC en el aula. Comunicar 2016, 24,

79–87. [CrossRef]

6. Garrote, D.; Arenas, J.A.; Jiménez-Fernández, S. ICT as tools for the development of intercultural competence.

EDMETIC 2018, 7, 166–183. [CrossRef]

7. Li, S.; Yamaguchi, S.; Sukhbaatar, J.; Takada, J. The Influence of Teachers’ Professional Development Activities

on the Factors Promoting ICT Integration in Primary Schools in Mongolia. Educ. Sci. 2019, 9, 78. [CrossRef]

8. Pereira, S.; Fillol, J.; Moura, P. El aprendizaje de los jóvenes con medios digitales fuera de la escuela: De lo

informal a lo formal. Comunicar 2019, 1, 41–50. [CrossRef]

9. Cabero, J.; Barroso, J. Los escenarios tecnológicos en Realidad Aumentada (RA): Posibilidades educativas en

estudios universitarios. Aula Abierta 2018, 47, 327–336. [CrossRef]

10. Nikolopoulou, K.; Akriotou, D.; Gialamas, V. Early Reading Skills in English as a Foreign Language Via ICT

in Greece: Early Childhood Student Teachers’ Perceptions. Early Child. Educ. J. 2019, 47, 597–606. [CrossRef]

11. Mat, N.S.; Abdul, A.; Mat, M.; Abdul, S.Z.; Nun, N.F.; Hamdan, A. An evaluation of content creation for

personalised learning using digital ICT literacy module among aboriginal students (MLICT-OA). TOJDE

2019, 20, 41–58.

12. Álvarez-Rodríguez, M.D.; Bellido-Márquez, M.D.; Atencia-Barrero, P. Teaching though ICT in Obligatory

Secundary Education. Analysis of online teaching tools. RED 2019, 1, 1–19. [CrossRef]

Table A1. Cont.

Socio-Educational Dimension

How does the methodology applied in the subject of mathematics affect

Graphics

the ability to analyse and represent graphs?

How much has the methodology applied in the subject of mathematics

contributed to your ability to analyse and represent graphs?

How does the methodology applied in the subject of mathematics affect

Results

the ability to interpret and reflect the results of the proposed activities?

To what extent has the methodology applied in the subject of

mathematics contributed to your ability to interpret and reflect the

results of the proposed activities?

How does the methodology applied in the subject of mathematics to

Decision

the development of mathematical competence?

To what extent has the methodology applied in the subject of

mathematics contributed to your ability to make decisions?

0–4.9

5–5.9

What is your average grade in general?

6–8.9

9–10

0–4.9

5–5.9

Ratings What is your general average in the Mathematics subject?

6–8.9

9–10

0–4.9

What has been the grade you have obtained in the Mathematics subject after 5–5.9

the development of the experience? 6–8.9

9–10

1. Alonso-García, S.; Aznar-Díaz, I.; Cáceres-Reche, M.P.; Trujillo-Torres, J.M.; Romero-Rodríguez, J.M.

Systematic Review of Good Teaching Practices with ICT in Spanish Higher Education. Trends and

Challenges for Sustainability. Sustainability 2019, 11, 7150. [CrossRef]

2. Hinojo, F.J.; Aznar, I.; Romero, J.M.; Marín, J.A. Influencia del aula invertida en el rendimiento académico.

Una revisión sistemática. Campus Virtuales 2019, 8, 9–18.

3. Hinojo, F.J.; Mingorance, A.C.; Trujillo, J.M.; Aznar, I.; Cáceres, M.P. Incidence of the flipped classroom in

the physical education students’ academic performance in university contexts. Sustainability 2018, 10, 1334.

[CrossRef]

4. Maldonado, G.A.; García, J.; Sampedro-Requena, B. The effect of ICT and social networks on university

students. RIED 2019, 22, 153–176. [CrossRef]

5. Area, M.; Hernández, V.; Sosa, J.J. Modelos de integración didáctica de las TIC en el aula. Comunicar 2016, 24,

79–87. [CrossRef]

6. Garrote, D.; Arenas, J.A.; Jiménez-Fernández, S. ICT as tools for the development of intercultural competence.

EDMETIC 2018, 7, 166–183. [CrossRef]

7. Li, S.; Yamaguchi, S.; Sukhbaatar, J.; Takada, J. The Influence of Teachers’ Professional Development Activities

on the Factors Promoting ICT Integration in Primary Schools in Mongolia. Educ. Sci. 2019, 9, 78. [CrossRef]

8. Pereira, S.; Fillol, J.; Moura, P. El aprendizaje de los jóvenes con medios digitales fuera de la escuela: De lo

informal a lo formal. Comunicar 2019, 1, 41–50. [CrossRef]

9. Cabero, J.; Barroso, J. Los escenarios tecnológicos en Realidad Aumentada (RA): Posibilidades educativas en

estudios universitarios. Aula Abierta 2018, 47, 327–336. [CrossRef]

10. Nikolopoulou, K.; Akriotou, D.; Gialamas, V. Early Reading Skills in English as a Foreign Language Via ICT

in Greece: Early Childhood Student Teachers’ Perceptions. Early Child. Educ. J. 2019, 47, 597–606. [CrossRef]

11. Mat, N.S.; Abdul, A.; Mat, M.; Abdul, S.Z.; Nun, N.F.; Hamdan, A. An evaluation of content creation for

personalised learning using digital ICT literacy module among aboriginal students (MLICT-OA). TOJDE

2019, 20, 41–58.

12. Álvarez-Rodríguez, M.D.; Bellido-Márquez, M.D.; Atencia-Barrero, P. Teaching though ICT in Obligatory

Secundary Education. Analysis of online teaching tools. RED 2019, 1, 1–19. [CrossRef]

14.
Mathematics 2020, 8, 840 14 of 16

13. Khine, M.S.; Ali, N.; Afari, E. Exploring relationships among TPACK constructs and ICT achievement among

trainee teachers. Educ. Infor. Technol. 2017, 22, 1605–1621. [CrossRef]

14. López-Quintero, J.L.; Pontes-Pedrajas, A.; Varo-Martínez, M. The role of ICT in Hispanic American scientific

and technological education: A review of literature. Dig. Educ. Rev. 2019, 1, 229–243.

15. Cole, M.T.; Swartz, L.B.; Shelley, D.J. Threaded Discussion: The Role It Plays in E-Learning. Int. J. Inf.

Commun. Technol. Educ. 2020, 16, 16–29. [CrossRef]

16. Baby, A.; Kannammal, A. Network Path Analysis for developing an enhanced TAM model: A user-centric

e-learning perspective. Comput. Hum. Behav. 2020, 107, 1–7. [CrossRef]

17. Wan, S.; Niu, Z. A Hybrid E-Learning Recommendation Approach Based on Learners’ Influence Propagation.

IEEE Trans. Knowl. Data Eng. 2020, 32, 827–840. [CrossRef]

18. Hamutoglu, N.B.; Savasci, M.; Sezen-Gultekin, G. Digital Literacy Skills and Attitudes towards E-learning.

J. Educ. Future 2019, 16, 93–107. [CrossRef]

19. Mian, A.; Khan, S. Medical education during pandemics: A UK perspective. BMC Med. 2020, 18, 1–2.

[CrossRef]

20. Qian, Y. Application Research of E-learning Network Teaching Platform in College English Reading Teaching.

Educ. Sci. -Theory & Pract. 2018, 18, 1819–1827. [CrossRef]

21. Khlifi, Y. An Advanced Authentication Scheme for E-evaluation Using Students Behaviors Over E-learning

Platform. Int. J. Emerg. Technol. Learn. 2020, 15, 90–111. [CrossRef]

22. Zhu, X.; Chen, Z. Dual-modality spatiotemporal feature learning for spontaneous facial expression recognition

in e-learning using hybrid deep neural network. Vis. Comput. 2020, 36, 743–755. [CrossRef]

23. Shakah, G.; Al-Oqaily; Alqudah, F. Motivation Path between the Difficulties and Attitudes of Using the

E-Learning Systems in the Jordanian Universities: Aajloun University as a Case Study. Int. J. Emerg.

Technol. Learn. 2019, 14, 26–48. [CrossRef]

24. Laskaris, D.; Heretakis, E.; Kalogiannakis, M.; Ampartzaki, M. Critical reflections on introducing e-learning

within a blended education context. Int. J. Technol. Enhanc. Learn. 2019, 11, 413–440. [CrossRef]

25. Aznar, I.; Cáceres, P.; Romero, J.M. Digital competence of an e-learning tutor: An emerging model of good

teaching practices in ICT. Texto Livre-Linguagem e Tecnologia 2019, 12, 49–68. [CrossRef]

26. Aghababaei, M.; Ardani, S. Trend of Changes in E-learning Role in Identity Changes, Achievement Emotions

and Attitude Toward School Between High School Students from Smart and Traditional Schools. Mod. J.

Lang. Teach. Methods 2018, 8, 570–586.

27. Wongwuttiwat, J.; Buraphadeja, V.; Tantontrakul, T. A case study of blended e-learning in Thailand. Interact.

Technol. Smart Educ. 2020, 1–19. [CrossRef]

28. Beinicke, A.; Bipp, T. Evaluating Training Outcomes in Corporate E-Learning and Classroom Training.

Vocat. Learn. 2018, 11, 501–528. [CrossRef]

29. Sathiyamoorthi, V. An Intelligent System for Predicting a User Access to a Web Based E-Learning System

Using Web Mining. Int. J. Inf. Technol. Web Eng. 2020, 15, 75–94. [CrossRef]

30. Luo, N.; Zhang, Y.; Zhang, M.L. Retaining learners by establishing harmonious relationships in e-learning

environment. Interact. Learn. Environ. 2019, 27, 118–131. [CrossRef]

31. Bakhouyi, A.; Dehbi, R.; Banane, M.; Talea, M. A Semantic Web Solution for Enhancing The Interoperability

of E-learning Systems by Using Next Generation of SCORM Specifications. Int. J. Emerg. Technol. Learn.

2019, 14, 174–185. [CrossRef]

32. Gunasinghe, A.; Abd Hamid, J.; Khatibi, A.; Azam, S.M.F. The adequacy of UTAUT-3 in interpreting

academician’s adoption to e-Learning in higher education environments. Interact. Technol. Smart Educ. 2019,

17, 86–106. [CrossRef]

33. Kalpokaite, N.; Radivojevic, I. Teaching qualitative data analysis software online: A comparison of face-to-face

and e-learning ATLAS.ti courses. Int. J. Res. Method Educ. 2019, 1–15. [CrossRef]

34. Mousavi, A.; Mohammadi, A.; Mojtahedzadeh, R.; Shirazi, M.; Rashidi, H. E-learning educational atmosphere

measure (EEAM): A new instrument for assessing e-students’ perception of educational environment.

Res. Learn. Technol. 2020, 28, 1–12. [CrossRef]

35. Mowla, S.; Kolekar, S.V. Development and Integration of E-learning Services Using REST APIs. Int. J. Emerg.

Technol. Learn. 2020, 15, 53–72. [CrossRef]

36. Rakic, S.; Tasic, N.; Marjanovic, U.; Softic, S.; Luftenegger, E.; Turcin, I. Student Performance on an E-Learning

Platform: Mixed Method Approach. Int. J. Emerg. Technol. Learn. 2020, 15, 187–203. [CrossRef]

13. Khine, M.S.; Ali, N.; Afari, E. Exploring relationships among TPACK constructs and ICT achievement among

trainee teachers. Educ. Infor. Technol. 2017, 22, 1605–1621. [CrossRef]

14. López-Quintero, J.L.; Pontes-Pedrajas, A.; Varo-Martínez, M. The role of ICT in Hispanic American scientific

and technological education: A review of literature. Dig. Educ. Rev. 2019, 1, 229–243.

15. Cole, M.T.; Swartz, L.B.; Shelley, D.J. Threaded Discussion: The Role It Plays in E-Learning. Int. J. Inf.

Commun. Technol. Educ. 2020, 16, 16–29. [CrossRef]

16. Baby, A.; Kannammal, A. Network Path Analysis for developing an enhanced TAM model: A user-centric

e-learning perspective. Comput. Hum. Behav. 2020, 107, 1–7. [CrossRef]

17. Wan, S.; Niu, Z. A Hybrid E-Learning Recommendation Approach Based on Learners’ Influence Propagation.

IEEE Trans. Knowl. Data Eng. 2020, 32, 827–840. [CrossRef]

18. Hamutoglu, N.B.; Savasci, M.; Sezen-Gultekin, G. Digital Literacy Skills and Attitudes towards E-learning.

J. Educ. Future 2019, 16, 93–107. [CrossRef]

19. Mian, A.; Khan, S. Medical education during pandemics: A UK perspective. BMC Med. 2020, 18, 1–2.

[CrossRef]

20. Qian, Y. Application Research of E-learning Network Teaching Platform in College English Reading Teaching.

Educ. Sci. -Theory & Pract. 2018, 18, 1819–1827. [CrossRef]

21. Khlifi, Y. An Advanced Authentication Scheme for E-evaluation Using Students Behaviors Over E-learning

Platform. Int. J. Emerg. Technol. Learn. 2020, 15, 90–111. [CrossRef]

22. Zhu, X.; Chen, Z. Dual-modality spatiotemporal feature learning for spontaneous facial expression recognition

in e-learning using hybrid deep neural network. Vis. Comput. 2020, 36, 743–755. [CrossRef]

23. Shakah, G.; Al-Oqaily; Alqudah, F. Motivation Path between the Difficulties and Attitudes of Using the

E-Learning Systems in the Jordanian Universities: Aajloun University as a Case Study. Int. J. Emerg.

Technol. Learn. 2019, 14, 26–48. [CrossRef]

24. Laskaris, D.; Heretakis, E.; Kalogiannakis, M.; Ampartzaki, M. Critical reflections on introducing e-learning

within a blended education context. Int. J. Technol. Enhanc. Learn. 2019, 11, 413–440. [CrossRef]

25. Aznar, I.; Cáceres, P.; Romero, J.M. Digital competence of an e-learning tutor: An emerging model of good

teaching practices in ICT. Texto Livre-Linguagem e Tecnologia 2019, 12, 49–68. [CrossRef]

26. Aghababaei, M.; Ardani, S. Trend of Changes in E-learning Role in Identity Changes, Achievement Emotions

and Attitude Toward School Between High School Students from Smart and Traditional Schools. Mod. J.

Lang. Teach. Methods 2018, 8, 570–586.

27. Wongwuttiwat, J.; Buraphadeja, V.; Tantontrakul, T. A case study of blended e-learning in Thailand. Interact.

Technol. Smart Educ. 2020, 1–19. [CrossRef]

28. Beinicke, A.; Bipp, T. Evaluating Training Outcomes in Corporate E-Learning and Classroom Training.

Vocat. Learn. 2018, 11, 501–528. [CrossRef]

29. Sathiyamoorthi, V. An Intelligent System for Predicting a User Access to a Web Based E-Learning System

Using Web Mining. Int. J. Inf. Technol. Web Eng. 2020, 15, 75–94. [CrossRef]

30. Luo, N.; Zhang, Y.; Zhang, M.L. Retaining learners by establishing harmonious relationships in e-learning

environment. Interact. Learn. Environ. 2019, 27, 118–131. [CrossRef]

31. Bakhouyi, A.; Dehbi, R.; Banane, M.; Talea, M. A Semantic Web Solution for Enhancing The Interoperability

of E-learning Systems by Using Next Generation of SCORM Specifications. Int. J. Emerg. Technol. Learn.

2019, 14, 174–185. [CrossRef]

32. Gunasinghe, A.; Abd Hamid, J.; Khatibi, A.; Azam, S.M.F. The adequacy of UTAUT-3 in interpreting

academician’s adoption to e-Learning in higher education environments. Interact. Technol. Smart Educ. 2019,

17, 86–106. [CrossRef]

33. Kalpokaite, N.; Radivojevic, I. Teaching qualitative data analysis software online: A comparison of face-to-face

and e-learning ATLAS.ti courses. Int. J. Res. Method Educ. 2019, 1–15. [CrossRef]

34. Mousavi, A.; Mohammadi, A.; Mojtahedzadeh, R.; Shirazi, M.; Rashidi, H. E-learning educational atmosphere

measure (EEAM): A new instrument for assessing e-students’ perception of educational environment.

Res. Learn. Technol. 2020, 28, 1–12. [CrossRef]

35. Mowla, S.; Kolekar, S.V. Development and Integration of E-learning Services Using REST APIs. Int. J. Emerg.

Technol. Learn. 2020, 15, 53–72. [CrossRef]

36. Rakic, S.; Tasic, N.; Marjanovic, U.; Softic, S.; Luftenegger, E.; Turcin, I. Student Performance on an E-Learning

Platform: Mixed Method Approach. Int. J. Emerg. Technol. Learn. 2020, 15, 187–203. [CrossRef]

15.
Mathematics 2020, 8, 840 15 of 16

37. Albuquerque, C.; Santos, R.N.; Lino, N.C.Q. A Self-Adjusting Approach for Temporal Dropout Prediction of

E-Learning Students. Int. J. Distance Educ. Technol. 2020, 18, 19–33. [CrossRef]

38. Waluyo, B. Learning Outcomes of a General English Course Implementing Multiple E-learning Technologies

and Active Learning Concepts. J. Asia TEFL 2020, 17, 160–181. [CrossRef]

39. Akugizibwe, E.; Yong, J. Perspectives for effective integration of e-learning tools in university mathematics

instruction for developing countries. Educ. Inf. Technol. 2020, 25, 889–903. [CrossRef]

40. Bheki, C. Is Moodle or WhatsApp the preferred e-learning platform at a South African university? First-year

students’ experiences. Educ. Inf. Technol. 2020, 25, 927–941. [CrossRef]

41. Lam, T.Y.; Dongol, B. A blockchain-enabled e-learning platform. Interact. Learn. Environ. 2020, 1–23.

[CrossRef]

42. Herodotou, C.; Rienties, B.; Hlosta, M.; Borrowa, A.; Mangafa, C.; Zdrahal, Z. The scalable implementation

of predictive learning analytics at a distance learning university: Insights from a longitudinal case study.

Internet High. Educ. 2020, 45, 1–13. [CrossRef]

43. Dwyer, C.P.; Walsh, A. An exploratory quantitative case study of critical thinking development through

adult distance learning. ETR&D—Educ. Technol. Res. Dev. 2020, 68, 17–35. [CrossRef]

44. Lazarova, S.; Lazarov, L. Distance Learning-Challenges and ways to achieve higher quality of training

courses. Pedagog. -Pedagog. 2020, 92, 323–341.

45. Viktorova, L.V. Educational conditions for implementation of adults’ distance learning of foreign languages.

Inf. Technol. Learn. Tools 2020, 75, 13–25.

46. Kayser, I.; Merz, T. Lone Wolves in Distance Learning? An Empirical Analysis of the Tendency to

Communicate Within Student Groups. Int. J. Mobile Blended Learn. 2020, 12, 1–13. [CrossRef]

47. Ashwin, T.S.; Reddy, R.M. Impact of inquiry interventions on students in e-learning and classroom

environments using affective computing framework. USER Modeling User-Adapt. Interact. 2020, 1–43.

[CrossRef]

48. Tan, S.M.; Liew, T.W.; Gan, C.L. Motivational virtual agent in e-learning: The roles of regulatory focus and

message framing. Inf. Learn. Sci. 2020, 121, 37–51. [CrossRef]

49. Hadoussa, S. Evaluation of e-learning system on higher education institutions in KSA: A survey at Saudi

Electronic University. Int. J. Technol. Enhanc. Learn. 2020, 12, 180–199. [CrossRef]

50. Ben, A.; Abid, M.; Meddeb, A. Secure Fog-Based E-Learning Scheme. IEEE Access 2020, 8, 31920–31933.

[CrossRef]

51. Vagarinho, J.P.; Llamas-Nistal, M. Process-Oriented Quality in e-Learning: A Proposal for a Global Model.

IEEE Access 2020, 8, 13710–13734. [CrossRef]

52. Cerezo, R.; Bogarin, A.; Esteban, M.; Romero, C. Process mining for self-regulated learning assessment in

e-learning. J. Comput. High. Educ. 2020, 32, 1–15. [CrossRef]

53. Moubayed, A.; Injadat, M.; Shami, A.; Lutfiyya, H. Student Engagement Level in e-Learning Environment:

Clustering Using K-means. Am. J. Distance Educ. 2020, 1–20. [CrossRef]

54. Karkar, A.J.M.; Fatlawi, H.K.; Al-Jobouri, A.A. Highlighting E-learning Adoption Challenges using data

Analysis Techniques: University of Kufa as a Case Study. Electron. J. E-learning 2020, 18, 136–149. [CrossRef]

55. Yaniawati, P.; Kariadinata, R.; Sarin, N.M.; Pramiarsih, E.E.; Mariani, M. Integration of e-Learning for

Mathematics on Resource-Based Learning: Increasing Mathematical Creative Thinking and Self-Confidence.

Int. J. Emerg. Technol. Learn. 2020, 15, 60–78. [CrossRef]

56. Williamson, T. Alternative logics and applied mathematics. Philos. Issues 2018, 28, 399–424. [CrossRef]

57. Carvajalino, J. Edwin Bidwell Wilson and Mathematics as Language. ISIS 2018, 109, 494–514. [CrossRef]

58. Acharjee, S. On Connections of Soft Set Theory with Existing Mathematics of Uncertainties: A Short

Discussion for Non-Mathematicians with Respect to Soft Set Theory. New Math. Nat. Comput. 2018, 14, 1–9.

[CrossRef]

59. Yagci, E.; Uluoz, T. Leadership Styles of School Administrators and its Relation with the Mobbing Experience

Levels of Social, Science and Mathematics Teachers. Eurasia J. Math. Sci. Technol. Educ. 2018, 14, 155–166.

[CrossRef]

60. Kartal, A.; Caglayan, K.T. A Buchet from Disciplines: SSSM (Social Sciences—Science—Mathematics).

Egitim ve Bilim-Educ. Sci. 2018, 43, 189–214. [CrossRef]

37. Albuquerque, C.; Santos, R.N.; Lino, N.C.Q. A Self-Adjusting Approach for Temporal Dropout Prediction of

E-Learning Students. Int. J. Distance Educ. Technol. 2020, 18, 19–33. [CrossRef]

38. Waluyo, B. Learning Outcomes of a General English Course Implementing Multiple E-learning Technologies

and Active Learning Concepts. J. Asia TEFL 2020, 17, 160–181. [CrossRef]

39. Akugizibwe, E.; Yong, J. Perspectives for effective integration of e-learning tools in university mathematics

instruction for developing countries. Educ. Inf. Technol. 2020, 25, 889–903. [CrossRef]

40. Bheki, C. Is Moodle or WhatsApp the preferred e-learning platform at a South African university? First-year

students’ experiences. Educ. Inf. Technol. 2020, 25, 927–941. [CrossRef]

41. Lam, T.Y.; Dongol, B. A blockchain-enabled e-learning platform. Interact. Learn. Environ. 2020, 1–23.

[CrossRef]

42. Herodotou, C.; Rienties, B.; Hlosta, M.; Borrowa, A.; Mangafa, C.; Zdrahal, Z. The scalable implementation

of predictive learning analytics at a distance learning university: Insights from a longitudinal case study.

Internet High. Educ. 2020, 45, 1–13. [CrossRef]

43. Dwyer, C.P.; Walsh, A. An exploratory quantitative case study of critical thinking development through

adult distance learning. ETR&D—Educ. Technol. Res. Dev. 2020, 68, 17–35. [CrossRef]

44. Lazarova, S.; Lazarov, L. Distance Learning-Challenges and ways to achieve higher quality of training

courses. Pedagog. -Pedagog. 2020, 92, 323–341.

45. Viktorova, L.V. Educational conditions for implementation of adults’ distance learning of foreign languages.

Inf. Technol. Learn. Tools 2020, 75, 13–25.

46. Kayser, I.; Merz, T. Lone Wolves in Distance Learning? An Empirical Analysis of the Tendency to

Communicate Within Student Groups. Int. J. Mobile Blended Learn. 2020, 12, 1–13. [CrossRef]

47. Ashwin, T.S.; Reddy, R.M. Impact of inquiry interventions on students in e-learning and classroom

environments using affective computing framework. USER Modeling User-Adapt. Interact. 2020, 1–43.

[CrossRef]

48. Tan, S.M.; Liew, T.W.; Gan, C.L. Motivational virtual agent in e-learning: The roles of regulatory focus and

message framing. Inf. Learn. Sci. 2020, 121, 37–51. [CrossRef]

49. Hadoussa, S. Evaluation of e-learning system on higher education institutions in KSA: A survey at Saudi

Electronic University. Int. J. Technol. Enhanc. Learn. 2020, 12, 180–199. [CrossRef]

50. Ben, A.; Abid, M.; Meddeb, A. Secure Fog-Based E-Learning Scheme. IEEE Access 2020, 8, 31920–31933.

[CrossRef]

51. Vagarinho, J.P.; Llamas-Nistal, M. Process-Oriented Quality in e-Learning: A Proposal for a Global Model.

IEEE Access 2020, 8, 13710–13734. [CrossRef]

52. Cerezo, R.; Bogarin, A.; Esteban, M.; Romero, C. Process mining for self-regulated learning assessment in

e-learning. J. Comput. High. Educ. 2020, 32, 1–15. [CrossRef]

53. Moubayed, A.; Injadat, M.; Shami, A.; Lutfiyya, H. Student Engagement Level in e-Learning Environment:

Clustering Using K-means. Am. J. Distance Educ. 2020, 1–20. [CrossRef]

54. Karkar, A.J.M.; Fatlawi, H.K.; Al-Jobouri, A.A. Highlighting E-learning Adoption Challenges using data

Analysis Techniques: University of Kufa as a Case Study. Electron. J. E-learning 2020, 18, 136–149. [CrossRef]

55. Yaniawati, P.; Kariadinata, R.; Sarin, N.M.; Pramiarsih, E.E.; Mariani, M. Integration of e-Learning for

Mathematics on Resource-Based Learning: Increasing Mathematical Creative Thinking and Self-Confidence.

Int. J. Emerg. Technol. Learn. 2020, 15, 60–78. [CrossRef]

56. Williamson, T. Alternative logics and applied mathematics. Philos. Issues 2018, 28, 399–424. [CrossRef]

57. Carvajalino, J. Edwin Bidwell Wilson and Mathematics as Language. ISIS 2018, 109, 494–514. [CrossRef]

58. Acharjee, S. On Connections of Soft Set Theory with Existing Mathematics of Uncertainties: A Short

Discussion for Non-Mathematicians with Respect to Soft Set Theory. New Math. Nat. Comput. 2018, 14, 1–9.

[CrossRef]

59. Yagci, E.; Uluoz, T. Leadership Styles of School Administrators and its Relation with the Mobbing Experience

Levels of Social, Science and Mathematics Teachers. Eurasia J. Math. Sci. Technol. Educ. 2018, 14, 155–166.

[CrossRef]

60. Kartal, A.; Caglayan, K.T. A Buchet from Disciplines: SSSM (Social Sciences—Science—Mathematics).

Egitim ve Bilim-Educ. Sci. 2018, 43, 189–214. [CrossRef]

16.
Mathematics 2020, 8, 840 16 of 16

61. Lewis, K.L.; Stout, J.G.; Finkelstein, N.D.; Pollock, S.J.; Miyake, A.; Cohen, G.L.; Ito, T.A. Fitting in to

Move Forward: Belonging, Gender, and Persistence in the Physical Sciences, Technology, Engineering, and

Mathematics (pSTEM). Psychol. Women Q. 2017, 41, 420–436. [CrossRef]

62. Paechter, M.; Macher, D.; Martskvishvili, K.; Wimmer, S.; Papousek, I. Mathematics Anxiety and Statistics

Anxiety. Shared but Also Unshared Components and Antagonistic Contributions to Performance in Statistics.

Front. Psychol. 2017, 8, 1–13. [CrossRef] [PubMed]

63. Titilope, E.A.; Idiong, U.S. Depression and anxiety: The bane of academic achievement among science

students offering mathematics. Med Sci. 2017, 21, 8–15.

64. Ahn, J.Y.; Edwin, A. An e-Learning Model for Teaching Mathematics on an Open Source Learning Platform.

Int. Rev. Res. Open Distrib. Learn. 2018, 19, 255–267. [CrossRef]

65. Albano, G.; Dello, U. GeoGebra in e-learning environments: A possible integration in mathematics and

beyond. J. Ambient Intell. Humaniz. Comput. 2019, 10, 4331–4343. [CrossRef]

66. El Mamoun, B.; Erradi, M.; El Mhouti, A. Using an Intelligent Tutoring System to Support Learners’ WMC in

e-learning: Application in Mathematics Learning. Int. J. Emerg. Technol. Learn. 2018, 13, 142–156. [CrossRef]

67. Nasrullah, A.; Marlina, M.; Dwiyanti, W. Development of Student Worksheet-Based College E-Learning

Through Edmodo to Maximize the Results of Learning and Motivation in Economic Mathematics Learning.

Int. J. Emerg. Technol. Learn. 2018, 13, 211–229. [CrossRef]

68. Mulqueeny, K.; Kostyuk, V.; Baker, R.S.; Ocumpaugh, J. Incorporating effective e-learning principles to

improve student engagement in middle-school mathematics. Int. J. STEM Educ. 2015, 2, 1–14. [CrossRef]

69. Ozyurt, O.; Ozyurt, H.; Baki, A.; Guven, B. Integration into mathematics classrooms of an adaptive

and intelligent individualized e-learning environment: Implementation and evaluation of UZWEBMAT.

Comput. Hum. Behav. 2013, 29, 726–738. [CrossRef]

70. Msomi, A.M.; Bansilal, S. The experiences for first-year students in mathematics in using an e-learning

platform a University of Technology. South J. High. Educ. 2018, 32, 124–139. [CrossRef]

71. Moreno-Guerrero, A.J. Estudio bibliométrico de la producción científica sobre la inspección educativa. REICE.

Revista Iberoameriocana sobre Calidad, Eficacia y Cambio en Educación 2019, 17, 23–40. [CrossRef]

72. Hernández, R.; Fernández, C.; Baptista, M.P. Metodología de la Investigación, 6th ed.; McGraw Hill: Madrid,

Spain, 2014; pp. 129–168.

73. Moreno-Guerrero, A.J.; Romero-Rodríguez, J.M.; López-Belmonte, J.; Alonso-García, S. Flipped Learning

Approach as Educational Innovation in Water Literacy. Water 2020, 12, 574. [CrossRef]

74. Moreno-Guerrero, A.J.; Rodríguez-Jiménez, C.; Gómez-García, G.; Ramos, M. Educational Innovation in

Higher Education: Use of Role Playing and Educational Video in Pre-service Teachers’ Training. Sustainability

2020, 12, 2558. [CrossRef]

75. Chou, P.N.; Feng, S.T. Using a Tablet Computer Application to Advance High School Students’ Laboratory

Learning Experiences: A Focus on Electrical Engineering Education. Sustainability 2019, 11, 381. [CrossRef]

76. Yılmaz, A.; Soyer, F. Effect of Physical Education and Play Applications on School Social Behaviors of

Mild-Level Intellectually Disabled Children. Educ. Sci. 2018, 8, 89. [CrossRef]

77. López, J.; Fuentes, A.; López, J.A.; Pozo, S. Formative Transcendence of Flipped Learning in Mathematics

Students of Secondary Education. Mathematics 2019, 7, 1226. [CrossRef]

78. Moreno-Guerrero, A.-J.; Rondón García, M.; Martínez Heredia, N.; Rodríguez-García, A.-M. Collaborative

Learning Based on Harry Potter for Learning Geometric Figures in the Subject of Mathematics. Mathematics

2020, 8, 369. [CrossRef]

79. Jöreskog, K.G. Analysis of ordinal variables 2: Cross-Sectional Data. In Structural Equation Modelling with

Lisrel 8.51; Friedrich-Schiller-University Jena: Jena, Germany, 2001; pp. 116–119.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access

article distributed under the terms and conditions of the Creative Commons Attribution

(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

61. Lewis, K.L.; Stout, J.G.; Finkelstein, N.D.; Pollock, S.J.; Miyake, A.; Cohen, G.L.; Ito, T.A. Fitting in to

Move Forward: Belonging, Gender, and Persistence in the Physical Sciences, Technology, Engineering, and

Mathematics (pSTEM). Psychol. Women Q. 2017, 41, 420–436. [CrossRef]

62. Paechter, M.; Macher, D.; Martskvishvili, K.; Wimmer, S.; Papousek, I. Mathematics Anxiety and Statistics

Anxiety. Shared but Also Unshared Components and Antagonistic Contributions to Performance in Statistics.

Front. Psychol. 2017, 8, 1–13. [CrossRef] [PubMed]

63. Titilope, E.A.; Idiong, U.S. Depression and anxiety: The bane of academic achievement among science

students offering mathematics. Med Sci. 2017, 21, 8–15.

64. Ahn, J.Y.; Edwin, A. An e-Learning Model for Teaching Mathematics on an Open Source Learning Platform.

Int. Rev. Res. Open Distrib. Learn. 2018, 19, 255–267. [CrossRef]

65. Albano, G.; Dello, U. GeoGebra in e-learning environments: A possible integration in mathematics and

beyond. J. Ambient Intell. Humaniz. Comput. 2019, 10, 4331–4343. [CrossRef]

66. El Mamoun, B.; Erradi, M.; El Mhouti, A. Using an Intelligent Tutoring System to Support Learners’ WMC in

e-learning: Application in Mathematics Learning. Int. J. Emerg. Technol. Learn. 2018, 13, 142–156. [CrossRef]

67. Nasrullah, A.; Marlina, M.; Dwiyanti, W. Development of Student Worksheet-Based College E-Learning

Through Edmodo to Maximize the Results of Learning and Motivation in Economic Mathematics Learning.

Int. J. Emerg. Technol. Learn. 2018, 13, 211–229. [CrossRef]

68. Mulqueeny, K.; Kostyuk, V.; Baker, R.S.; Ocumpaugh, J. Incorporating effective e-learning principles to

improve student engagement in middle-school mathematics. Int. J. STEM Educ. 2015, 2, 1–14. [CrossRef]

69. Ozyurt, O.; Ozyurt, H.; Baki, A.; Guven, B. Integration into mathematics classrooms of an adaptive

and intelligent individualized e-learning environment: Implementation and evaluation of UZWEBMAT.

Comput. Hum. Behav. 2013, 29, 726–738. [CrossRef]

70. Msomi, A.M.; Bansilal, S. The experiences for first-year students in mathematics in using an e-learning

platform a University of Technology. South J. High. Educ. 2018, 32, 124–139. [CrossRef]

71. Moreno-Guerrero, A.J. Estudio bibliométrico de la producción científica sobre la inspección educativa. REICE.

Revista Iberoameriocana sobre Calidad, Eficacia y Cambio en Educación 2019, 17, 23–40. [CrossRef]

72. Hernández, R.; Fernández, C.; Baptista, M.P. Metodología de la Investigación, 6th ed.; McGraw Hill: Madrid,

Spain, 2014; pp. 129–168.

73. Moreno-Guerrero, A.J.; Romero-Rodríguez, J.M.; López-Belmonte, J.; Alonso-García, S. Flipped Learning

Approach as Educational Innovation in Water Literacy. Water 2020, 12, 574. [CrossRef]

74. Moreno-Guerrero, A.J.; Rodríguez-Jiménez, C.; Gómez-García, G.; Ramos, M. Educational Innovation in

Higher Education: Use of Role Playing and Educational Video in Pre-service Teachers’ Training. Sustainability

2020, 12, 2558. [CrossRef]

75. Chou, P.N.; Feng, S.T. Using a Tablet Computer Application to Advance High School Students’ Laboratory

Learning Experiences: A Focus on Electrical Engineering Education. Sustainability 2019, 11, 381. [CrossRef]

76. Yılmaz, A.; Soyer, F. Effect of Physical Education and Play Applications on School Social Behaviors of

Mild-Level Intellectually Disabled Children. Educ. Sci. 2018, 8, 89. [CrossRef]

77. López, J.; Fuentes, A.; López, J.A.; Pozo, S. Formative Transcendence of Flipped Learning in Mathematics

Students of Secondary Education. Mathematics 2019, 7, 1226. [CrossRef]

78. Moreno-Guerrero, A.-J.; Rondón García, M.; Martínez Heredia, N.; Rodríguez-García, A.-M. Collaborative

Learning Based on Harry Potter for Learning Geometric Figures in the Subject of Mathematics. Mathematics

2020, 8, 369. [CrossRef]

79. Jöreskog, K.G. Analysis of ordinal variables 2: Cross-Sectional Data. In Structural Equation Modelling with

Lisrel 8.51; Friedrich-Schiller-University Jena: Jena, Germany, 2001; pp. 116–119.

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