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Applied Sciences
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ICT and Statistics in Education
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ICT and Statistics in Education

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 51036

Special Issue Editors

Prof. Dr. Jenny Pange

E-Mail Website
Guest Editor
Lab of NT and Distance Learning, School of Education, University of Ioannina, Ioannina, Greece
Interests: ICT; e-learning; applied statistics
Special Issues, Collections and Topics in MDPI journals
Dr. Zoi Nikiforidou

E-Mail Website
Guest Editor
Early Childhood, Faculty of Education, Liverpool Hope University, Liverpool, UK
Interests: My research interests incorporate both methodological and theoretical issues on teaching and learning as well as aspects of cognitive development in early childhood: reasoning, perception, risk-taking

Special Issue Information

Dear Colleagues,

The idea behind publishing this Special Issue is not to predict the future of teaching ICTs and statistics but to foresee the great potential of using ICTs and statistics in education.

The changes that entail the transition from teaching through ICTs to sustainable educational applications using ICTs is often followed by the strength in adopting them. The unprecedented public health crisis with the COVID-19 pandemic has given us a small taste of such a point, with its impact on teaching, learning, and the transition to online education in general. Education won’t be the same in the post-COVID-19 era. Learning will no longer be all about teaching but on developing a new learning environment and a reliable cooperative discovery-based understanding of new concepts in unpredictable situations.

Furthermore, it is the first time where data and statistical analysis are playing such an important role in education and the economy. The importance of teaching statistics and data analysis is where we should focus on. But, first, we need to start with rich educational scenarios on teaching statistics in all educational levels.


Classroom studies, case studies, and teaching practices involving ICTs in education and teaching statistics are welcome. The planned Special Issue aims to explore this field.

Prof. Dr. Jenny Pange
Dr. Zoi Nikiforidou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ICT
  • statistics
  • education
  • teaching
  • learning

Published Papers (17 papers)

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Research

20 pages, 3403 KiB  
Article
Modeling Job Satisfaction of Peruvian Basic Education Teachers Using Machine Learning Techniques
by Luis Alberto Holgado-Apaza, Edgar E. Carpio-Vargas, Hugo D. Calderon-Vilca, Joab Maquera-Ramirez, Nelly J. Ulloa-Gallardo, María Susana Acosta-Navarrete, José Miguel Barrón-Adame, Marleny Quispe-Layme, Rossana Hidalgo-Pozzi and Miguel Valles-Coral
Appl. Sci. 2023, 13(6), 3945; https://0-doi-org.brum.beds.ac.uk/10.3390/app13063945 - 20 Mar 2023
Cited by 1 | Viewed by 3209
Abstract
Teacher job satisfaction is an important aspect of academic performance, student retention, and teacher retention. We propose to determine the predictive model of job satisfaction of basic education teachers using machine learning techniques. The original data set consisted of 15,087 instances and 942 [...] Read more.
Teacher job satisfaction is an important aspect of academic performance, student retention, and teacher retention. We propose to determine the predictive model of job satisfaction of basic education teachers using machine learning techniques. The original data set consisted of 15,087 instances and 942 attributes from the national survey of teachers from public and private educational institutions of regular basic education (ENDO-2018) carried out by the Ministry of Education of Peru. We used the ANOVA F-test filter and the Chi-Square filter as feature selection techniques. In the modeling phase, the logistic regression algorithms, Gradient Boosting, Random Forest, XGBoost and Decision Trees-CART were used. Among the algorithms evaluated, XGBoost and Random Forest stand out, obtaining similar results in 4 of the 8 metrics evaluated, these are: balanced accuracy of 74%, sensitivity of 74%, F1-Score of 0.48 and negative predictive value of 0.94. However, in terms of the area under the ROC curve, XGBoost scores 0.83, while Random Forest scores 0.82. These algorithms also obtain the highest true-positive values (479 instances) and lowest false-negative values (168 instances) in the confusion matrix. Economic income, satisfaction with life, self-esteem, teaching activity, relationship with the director, perception of living conditions, family relationships; health problems related to depression and satisfaction with the relationship with colleagues turned out to be the most important predictors of job satisfaction in basic education teachers. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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20 pages, 1055 KiB  
Article
An SEM Model of Learning Engagement and Basic Mathematical Competencies Based on Experiential Learning
by Lu Sun and Longhai Xiao
Appl. Sci. 2023, 13(6), 3650; https://0-doi-org.brum.beds.ac.uk/10.3390/app13063650 - 13 Mar 2023
Viewed by 1824
Abstract
Primary school mathematics is one of the most important subjects in primary school learning, and basic mathematical competencies are an important component of the response to academic achievement. Improving students’ basic competence in mathematics is one of the important goals of teaching mathematics [...] Read more.
Primary school mathematics is one of the most important subjects in primary school learning, and basic mathematical competencies are an important component of the response to academic achievement. Improving students’ basic competence in mathematics is one of the important goals of teaching mathematics in primary schools. Research has shown that experiential learning has an impact on basic competencies in mathematics, attitudes toward mathematics, and self-efficacy in mathematics. Therefore, this study explores the structural model that fits the relationship between experiential learning and basic competencies in mathematics using a linear model. This study uses a sample of 263 primary school students to explore the influential relationships between learning engagement, mathematical attitudes, mathematical self-efficacy, and basic mathematical competencies after experiential learning. The study revealed that the model had a good fit, with learning engagement, mathematical attitudes, and mathematical self-efficacy all having significant effects on basic mathematical competencies; in addition, behavioral engagement had insignificant effects on mathematical attitudes and mathematical self-efficacy. This study can infer through one year of experiential learning and based on the structural model developed that experiential learning in mathematics can increase students’ learning engagement in mathematics learning and positively influence mathematical attitudes and mathematical self-efficacy, thus positively influencing students’ performance in basic mathematical competencies. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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15 pages, 287 KiB  
Article
Errors concerning Statistics and Probability in Spanish Secondary School Textbooks
by Nuria Rico and Juan F. Ruiz-Hidalgo
Appl. Sci. 2022, 12(24), 12719; https://0-doi-org.brum.beds.ac.uk/10.3390/app122412719 - 12 Dec 2022
Viewed by 1158
Abstract
Textbooks are considered essential, providing a hierarchical organisation of knowledge, forging the intellectual scaffolding of students and teachers alike, and playing a crucial role in compulsory education. In this paper we discuss, by means of a content analysis, the systematic errors detected in [...] Read more.
Textbooks are considered essential, providing a hierarchical organisation of knowledge, forging the intellectual scaffolding of students and teachers alike, and playing a crucial role in compulsory education. In this paper we discuss, by means of a content analysis, the systematic errors detected in the presentation of questions related to statistics and probability in Spanish secondary school textbooks on mathematics. We found some errors appear systematically in the texts, and the most common are: faulty differentiation between quantitative and qualitative variables, between discrete and continuous variables and between randomness and determinism, confused examples for the bar charts, uncritical choice for graphic representations, inaccuracies in specific vocabulary, and ignoring prior probabilities and a poor consideration about representativeness. We classify the observed errors considering that some of these errors arise from the inherent difficulty of the content and others arise from differences between mathematical and statistical thinking as well as from judgments based on heuristic rules. Knowing the existence of these errors and the reasons why they occur are key points to make them disappear from statistical lessons and to help citizens achieving true statistical literacy. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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13 pages, 921 KiB  
Article
Towards Closing STEAM Diversity Gaps: A Grey Review of Existing Initiatives
by Henry Hasti, Daniel Amo-Filva, David Fonseca, Sonia Verdugo-Castro, Alicia García-Holgado and Francisco José García-Peñalvo
Appl. Sci. 2022, 12(24), 12666; https://0-doi-org.brum.beds.ac.uk/10.3390/app122412666 - 10 Dec 2022
Cited by 2 | Viewed by 1406
Abstract
Although STEAM (science, technology, engineering, art, and math) and student-centered instruction are growing rapidly in popularity, their reach is not adequately distributed across diversity groups (including individuals of different genders, economic backgrounds, immigrant backgrounds, abilities, and races, among other characteristics). The CreaSTEAM project [...] Read more.
Although STEAM (science, technology, engineering, art, and math) and student-centered instruction are growing rapidly in popularity, their reach is not adequately distributed across diversity groups (including individuals of different genders, economic backgrounds, immigrant backgrounds, abilities, and races, among other characteristics). The CreaSTEAM project intends to address diversity gaps by developing STEAM-Labs, student-centered spaces that combine components of fab labs, media labs, and user labs to specifically target diversity gaps. This paper carried out an informal PRISMA systematic review of a collection of 124 worldwide STEAM diversity initiatives to gather data on existing best practices that will be used in the STEAM-Labs. The review studied the geographic distributions, organizational structures, founding years, and activity offerings of the initiatives, along with the dataset’s overall STEAM content area prevalence and diversity target area prevalence. STEM was the most common approach, and gender was the most common diversity target area. Since 2010 initiative creation has increased, with most growth in gender-focused initiatives. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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14 pages, 502 KiB  
Article
Switching Learning Methods during the Pandemic: A Quasi-Experimental Study on a Master Course
by Vita Santa Barletta, Fabio Cassano, Agostino Marengo, Alessandro Pagano, Jenny Pange and Antonio Piccinno
Appl. Sci. 2022, 12(17), 8438; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178438 - 24 Aug 2022
Cited by 13 | Viewed by 1994
Abstract
The COVID-19 pandemic marked an important breakthrough in human progress: from working habits to social life, the world population’s behaviours changed according to the new lifestyle requirements. In this changing environment, university courses and learning methods evolved along with other “remote” working activities. [...] Read more.
The COVID-19 pandemic marked an important breakthrough in human progress: from working habits to social life, the world population’s behaviours changed according to the new lifestyle requirements. In this changing environment, university courses and learning methods evolved along with other “remote” working activities. For this quasi-experimental study, we discuss the effectiveness of the changes made by the LUMSA University in Rome, comparing two different groups of students who attended a master’s course with blended and fully remote methodologies. Here, we focused our attention on the paradigm shift, comparing the data gathered during the blended course in the 2019/2020 academic year with data gathered during the same course, but conducted fully online, in the academic year 2020/2021. Considering the sample size and type, the group comparison was made using a non-parametric test (U-test). The statistical analysis results suggest that there was no substantial difference between the students’ performance, confirming that the course changes made to adapt to the pandemic situation were successful and that learning effectiveness was preserved. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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20 pages, 6009 KiB  
Article
Coping with Access Difficulties and Absenteeism through Data Visualization: A Case Study from a Rural Vocational School in Northern Greece
by Christos Samaras, Rozita Tsoni, Evgenia Paxinou, Sotiris Kotsiantis and Vassilios S. Verykios
Appl. Sci. 2022, 12(14), 6946; https://0-doi-org.brum.beds.ac.uk/10.3390/app12146946 - 08 Jul 2022
Viewed by 2293
Abstract
Absenteeism and early school leaving (ESL) constitute two main problems in education with a significant impact on adolescents’ life. Early leavers from education and training may face considerable difficulties in the labor market later as adults. Motivated by the necessity of minimizing this [...] Read more.
Absenteeism and early school leaving (ESL) constitute two main problems in education with a significant impact on adolescents’ life. Early leavers from education and training may face considerable difficulties in the labor market later as adults. Motivated by the necessity of minimizing this phenomenon, we developed a novel application that uses big data, generated from a student attendance management system in a vocational senior high school in Greece. This application first automatically conducts data preprocessing and data transformation and saves the processed data on a cloud data warehouse. Then, an online analytical processing (OLAP) analysis is performed, resulting in a real-time visualization that provides a variety of different graphs. In this study, we demonstrate the need for real-time visualization of the analyzed data. Such a type of presentation provides information on the spot regarding potential early leavers’ behavior, helping school administrators gain time for prompt and effective actions. Through the data processing and analysis, the application provides instructors with constant information, in addition to those acquired by the formal student attendance management systems. Our research provides indicative evidence in favor of the use of such applications, as by adequately reacting to the observed patterns in real-time, we observed a significant decrease in students’ unnecessary absences and a reduction of the ELS phenomenon in a three-year school period. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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26 pages, 1434 KiB  
Article
Factors Influencing YouTube as a Learning Tool and Its Influence on Academic Achievement in a Bilingual Environment Using Extended Information Adoption Model (IAM) with ML Prediction—Jordan Case Study
by Evon Abu-Taieh, Issam AlHadid, Ra’ed Masa’deh, Rami S. Alkhawaldeh, Sufian Khwaldeh and Ala’aldin Alrowwad
Appl. Sci. 2022, 12(12), 5856; https://0-doi-org.brum.beds.ac.uk/10.3390/app12125856 - 09 Jun 2022
Cited by 17 | Viewed by 6798
Abstract
YouTube usage as a learning tool is evident among students. Hence, the goal of this study is to examine the various factors that influence the use of YouTube as a learning tool, which influences academic achievement in a bilingual academic context. Using survey [...] Read more.
YouTube usage as a learning tool is evident among students. Hence, the goal of this study is to examine the various factors that influence the use of YouTube as a learning tool, which influences academic achievement in a bilingual academic context. Using survey data from 704 YouTube users from Jordan’s bilingual academic institutes, the research model was empirically validated. Using Amos 20, structural equation modeling (SEM) was performed to assess the study hypotheses. SEM permits concurrent checking of the direct and indirect effects of all hypotheses. Confirmatory factor analysis (CFA) was used to validate the instrument items’ properties in addition to machine learning methods: ANN, SMO, the bagging reduced error pruning tree (RepTree), and random forest. The empirical results offer several key findings: academic achievement (AA) is influenced by the information adoption (IA) of YouTube as a learning tool. Information adoption (IA) is influenced by information usefulness (IU). Source credibility (SC) and information quality (IQ) both influence information usefulness (IU), while information language (IL) does not. Information quality (IQ) is influenced by intrinsic, contextual, and accessibility information quality. This study adds to the literature by empirically testing and theorizing the effects of YouTube as a learning tool on the academic achievement of Jordanian university students who are studying in bilingual surroundings. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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17 pages, 947 KiB  
Article
Impacts of Learning Orientation on the Modeling of Programming Using Feature Selection and XGBOOST: A Gender-Focused Analysis
by HoSung Woo and Ja-Mee Kim
Appl. Sci. 2022, 12(10), 4922; https://0-doi-org.brum.beds.ac.uk/10.3390/app12104922 - 12 May 2022
Cited by 2 | Viewed by 1497
Abstract
In programming, modeling is a generalized explanatory system that organizes key characteristics of a specific matter or object of interest using computer science concepts. Modeling is integral for both automation design in programming education and communication in the collaborative process. This study investigates [...] Read more.
In programming, modeling is a generalized explanatory system that organizes key characteristics of a specific matter or object of interest using computer science concepts. Modeling is integral for both automation design in programming education and communication in the collaborative process. This study investigates the effect of learning orientation on the modeling stage based on gender. The study includes 756 male and 688 female elementary-school students. We analyzed the results of XGBOOST by extracting the influential characteristics from feature selection along with the basic statistics. As a result of the study, it was confirmed that learners, regardless of gender, had the largest gap in modeling and that this was the stage at which differences occurred in programming education. For male students, the process of collecting data for modeling or devising a solution was found to be an important learning method. This shows that it is necessary to create an environment to focus on activities that derive solutions from the collected data along with strengthening information retrieval education. Although female students showed a similar tendency to male students, the process of cooperating with friends as a differentiating factor was found to be an important learning method. It seems necessary to apply teaching and learning methods that can strengthen team projects that can collaborate with friends. The findings could serve as a reference for teaching and learning design and operation for effective programming education. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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19 pages, 514 KiB  
Article
Cognitive Diagnostic Assessment in University Statistics Education: Valid and Reliable Skill Measurement for Actionable Feedback Using Learning Dashboards
by Lientje Maas, Matthieu J. S. Brinkhuis, Liesbeth Kester and Leoniek Wijngaards-de Meij
Appl. Sci. 2022, 12(10), 4809; https://0-doi-org.brum.beds.ac.uk/10.3390/app12104809 - 10 May 2022
Cited by 2 | Viewed by 2091
Abstract
E-learning is increasingly used to support student learning in higher education, facilitating administration of online formative assessments. Although providing diagnostic, actionable feedback is generally more effective, in current practice, feedback is often given in the form of a simple proportion of correctly solved [...] Read more.
E-learning is increasingly used to support student learning in higher education, facilitating administration of online formative assessments. Although providing diagnostic, actionable feedback is generally more effective, in current practice, feedback is often given in the form of a simple proportion of correctly solved items. This study shows the validation process of constructing detailed diagnostic information on a set of skills, abilities, and cognitive processes (so-called attributes) from students’ item response data with diagnostic classification models. Attribute measurement in the domain of statistics education is validated based on both expert judgment and empirical student data from a think-aloud study and large-scale assessment administration. The constructed assessments provide a valid and reliable measurement of the attributes. Inferences that can be drawn from the results of these formative assessments are discussed and it is demonstrated how this information can be communicated to students via learning dashboards to allow them to make more effective learning choices. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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17 pages, 1330 KiB  
Article
Evaluation of Applications for Mobile Devices on the Practice of Physical Exercise in Adolescents
by Diego Alonso-Fernández, Águeda Gutiérrez-Sánchez, Iago Portela-Pino and Yaiza Taboada-Iglesias
Appl. Sci. 2022, 12(6), 2784; https://0-doi-org.brum.beds.ac.uk/10.3390/app12062784 - 08 Mar 2022
Cited by 4 | Viewed by 1563
Abstract
The use of mobile devices has changed the way we relate to each other, influencing teaching–learning processes and the motivation of adolescents towards these processes. One of the most developed tools has been applications (apps), which are software used on cell phones, tablets [...] Read more.
The use of mobile devices has changed the way we relate to each other, influencing teaching–learning processes and the motivation of adolescents towards these processes. One of the most developed tools has been applications (apps), which are software used on cell phones, tablets or computers. Hence, the aim of this study is to analyze the content of applications for mobile devices that is considered the most suitable complement to Physical Education (PE) classes for secondary school students. A retrospective descriptive study was carried out, collecting information on the main characteristics of 31 free fitness apps: the descriptive, technical, educational and psychological dimensions. The results of this study show that most of the apps for physical activity have recent updates and are mainly related to cardiovascular exercise or strength for two purposes: either for exercise accounting or the creation of training plans for the user. They are intended for users of very heterogeneous ages and, therefore, do not take into account their individual characteristics. They do not have an adequate design to facilitate their didactic use. Therefore, we conclude that the applications evaluated lack the necessary educational potential to be used in the PE classroom. Based on the content analysis carried out, we describe a series of criteria that allow teachers and adolescents themselves to select physical exercise apps, and we propose to carry out research to guide developers when developing digital training/physical exercise content with an educational component that can be used as a complement for adolescents in- and outside the field of PE. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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10 pages, 262 KiB  
Article
Rating a Researcher’s Cumulative Scholarly Output Based on Their Sequence Numbers in Multi-Authored Publications
by Asif Iqbal and Quentin Cheok
Appl. Sci. 2022, 12(4), 1846; https://0-doi-org.brum.beds.ac.uk/10.3390/app12041846 - 10 Feb 2022
Cited by 1 | Viewed by 1240
Abstract
As the academic world yields an ever-increasing research output in terms of journal papers, conference proceedings, and books, the rating of published works and authors becomes imperative. All the big citation databases and search engines are currently using cumulative output indices, such as [...] Read more.
As the academic world yields an ever-increasing research output in terms of journal papers, conference proceedings, and books, the rating of published works and authors becomes imperative. All the big citation databases and search engines are currently using cumulative output indices, such as h-index, i10-index, and g-index, which do not consider the number of co-authors or the researcher’s sequence number in the authors list of a publication. In this context, the article presents a novel computational approach for evaluating a researcher’s scholarly output by taking into account the total number of co-authors, the sequence number of the researcher in the authors list, and the number of citations received per year by an article. Arithmetic progression is applied to quantify the credit for each co-author of a publication. The respective credits of a researcher are then accumulated for all their publications to obtain the rating. The method yields a truer value of the researcher’s impact in terms of their scholarly activities. A global implementation of the metric presented in this work will curb the unethical practice of including the names of non-contributing researchers in the authors list and expecting reciprocity in return. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
16 pages, 1308 KiB  
Article
Toward Predicting Student’s Academic Performance Using Artificial Neural Networks (ANNs)
by Yahia Baashar, Gamal Alkawsi, Abdulsalam Mustafa, Ammar Ahmed Alkahtani, Yazan A. Alsariera, Abdulrazzaq Qasem Ali, Wahidah Hashim and Sieh Kiong Tiong
Appl. Sci. 2022, 12(3), 1289; https://0-doi-org.brum.beds.ac.uk/10.3390/app12031289 - 26 Jan 2022
Cited by 31 | Viewed by 6788
Abstract
Student performance is related to complex and correlated factors. The implementation of a new advancement of technologies in educational displacement has unlimited potentials. One of these advances is the use of analytics and data mining to predict student academic accomplishment and performance. Given [...] Read more.
Student performance is related to complex and correlated factors. The implementation of a new advancement of technologies in educational displacement has unlimited potentials. One of these advances is the use of analytics and data mining to predict student academic accomplishment and performance. Given the existing literature, machine learning (ML) approaches such as Artificial Neural Networks (ANNs) can continuously be improved. This work examines and surveys the current literature regarding the ANN methods used in predicting students’ academic performance. This study also attempts to capture a pattern of the most used ANN techniques and algorithms. Of note, the articles reviewed mainly focused on higher education. The results indicated that ANN is always used in combination with data analysis and data mining methodologies, allowing studies to assess the effectiveness of their findings in evaluating academic achievement. No pattern was detected regarding selecting the input variables as they are mainly based on the context of the study and the availability of data. Moreover, the very limited tangible findings referred to the use of techniques in the actual context and target objective of improving student outcomes, performance, and achievement. An important recommendation of this work is to overcome the identified gap related to the only theoretical and limited application of the ANN in a real-life situation to help achieve the educational goals. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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21 pages, 3033 KiB  
Article
Leveraging AI and Machine Learning for National Student Survey: Actionable Insights from Textual Feedback to Enhance Quality of Teaching and Learning in UK’s Higher Education
by Raheel Nawaz, Quanbin Sun, Matthew Shardlow, Georgios Kontonatsios, Naif R. Aljohani, Anna Visvizi and Saeed-Ul Hassan
Appl. Sci. 2022, 12(1), 514; https://0-doi-org.brum.beds.ac.uk/10.3390/app12010514 - 05 Jan 2022
Cited by 14 | Viewed by 5008
Abstract
Students’ evaluation of teaching, for instance, through feedback surveys, constitutes an integral mechanism for quality assurance and enhancement of teaching and learning in higher education. These surveys usually comprise both the Likert scale and free-text responses. Since the discrete Likert scale responses are [...] Read more.
Students’ evaluation of teaching, for instance, through feedback surveys, constitutes an integral mechanism for quality assurance and enhancement of teaching and learning in higher education. These surveys usually comprise both the Likert scale and free-text responses. Since the discrete Likert scale responses are easy to analyze, they feature more prominently in survey analyses. However, the free-text responses often contain richer, detailed, and nuanced information with actionable insights. Mining these insights is more challenging, as it requires a higher degree of processing by human experts, making the process time-consuming and resource intensive. Consequently, the free-text analyses are often restricted in scale, scope, and impact. To address these issues, we propose a novel automated analysis framework for extracting actionable information from free-text responses to open-ended questions in student feedback questionnaires. By leveraging state-of-the-art supervised machine learning techniques and unsupervised clustering methods, we implemented our framework as a case study to analyze a large-scale dataset of 4400 open-ended responses to the National Student Survey (NSS) at a UK university. These analyses then led to the identification, design, implementation, and evaluation of a series of teaching and learning interventions over a two-year period. The highly encouraging results demonstrate our approach’s validity and broad (national and international) application potential—covering tertiary education, commercial training, and apprenticeship programs, etc., where textual feedback is collected to enhance the quality of teaching and learning. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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9 pages, 540 KiB  
Article
Content Analysis of Mobile Device Applications for Artistic Creation for Children between 4 and 12 Years of Age
by Sara Domínguez-Lloria, Rut Martínez López de Castro, Sara Fernández-Aguayo and Margarita Pino-Juste
Appl. Sci. 2021, 11(23), 11327; https://0-doi-org.brum.beds.ac.uk/10.3390/app112311327 - 30 Nov 2021
Viewed by 1406
Abstract
This article presents the results of the content analysis of 32 painting and drawing mobile applications aimed at children between 4 and 12 years old. The characteristics of the artistic dimension were studied, such as the possibilities of drawing, color, and experimentation, as [...] Read more.
This article presents the results of the content analysis of 32 painting and drawing mobile applications aimed at children between 4 and 12 years old. The characteristics of the artistic dimension were studied, such as the possibilities of drawing, color, and experimentation, as well as the characteristics of the technical dimension related to the visual design of the interface, usability, and adaptability to users. The results collected show that mobile apps offer tools that have great potential for artistic and creative development, but also reveal certain limitations and problems in the quality of the graphic tools and interface design. One of the central problems of the interfaces of these apps is related to decontextualization and the lack of attention to the diversity and the heterogeneity of users in that age group. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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16 pages, 1997 KiB  
Article
Vlog-Based Multimodal Composing: Enhancing EFL Learners’ Writing Performance
by Qiuzhu Xie, Xiaobin Liu, Nanyan Zhang, Qianqian Zhang, Xijuan Jiang and Lijun Wen
Appl. Sci. 2021, 11(20), 9655; https://0-doi-org.brum.beds.ac.uk/10.3390/app11209655 - 16 Oct 2021
Cited by 3 | Viewed by 2678
Abstract
For most learners of English as a foreign language (EFL), there has long been a lack of effective opportunities to practice English writing skills. However, the recent development of social networking services (SNS) provides new possibilities for these learners to practice writing English [...] Read more.
For most learners of English as a foreign language (EFL), there has long been a lack of effective opportunities to practice English writing skills. However, the recent development of social networking services (SNS) provides new possibilities for these learners to practice writing English in a meaningful way. Meanwhile, with the popularity of social media in language learning, writing is unnecessarily in the form of plain text, and multimodal composing based on text and additional modes such as audio, video or images has been a new form of writing activity instead. This study integrated SNS-based multimodal composing activities into secondary and higher education, with the aim of determining its effects on learners’ writing performance. Two classes in senior high school Grade 10 and four in college were recruited, three as the control groups without using SNS-based multimodal composing, and others as the experimental groups. While all classes’ writing performance improved between pretest and posttest, the gains in overall writing competence by experimental groups and the gains in three detailed aspects (readability, lexical complexity and syntactic complexity) by college students were significantly larger. Progress in detailed aspects, on the other hand, was different across different groups. These findings are discussed in relation to specific characteristics of multimodal composing and SNS-based learning that enables learners to improve writing performance. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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20 pages, 1217 KiB  
Article
Student eXperience: A Systematic Literature Review
by Nicolás Matus, Cristian Rusu and Sandra Cano
Appl. Sci. 2021, 11(20), 9543; https://0-doi-org.brum.beds.ac.uk/10.3390/app11209543 - 14 Oct 2021
Cited by 11 | Viewed by 5105
Abstract
Students’ experiences have been covered by a large number of studies in different areas. Even so, the concept of student experience (SX) is diffuse, as it does not have a widely accepted meaning and is often shaped to the specific purposes of each [...] Read more.
Students’ experiences have been covered by a large number of studies in different areas. Even so, the concept of student experience (SX) is diffuse, as it does not have a widely accepted meaning and is often shaped to the specific purposes of each study. Understanding this concept allows educational institutions to better address the needs of students. For this reason, we conducted a systematic literature review addressing the concept of SX in higher education, specifically aiming at undergraduate students. In this work, we approach the concept of SX from the perspective of customer experience (CX), based on the premise that students are users of higher education institutions’ products, systems and/or services. We reviewed articles published between 2011 and 2021, indexed in five databases (Scopus, Web of Sciences, ACM digital, IEEE Xplore and Science Direct), trying to address research questions concerning: (1) the SX definition; (2) dimensions, attributes and factors that influence SX; and (3) methods used to evaluate the SX. We selected 65 articles and analyzed various SX definitions, as well as scales and surveys to evaluate SX, mainly relating to satisfaction and quality in higher education. We propose a holistic definition of SX and recommend ways to achieve its better analysis. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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Article
Exploring Students’ Perceived Attitude on Utilizing a Biofeedback System for Anxiety Awareness during Academic Examination Activities
by Hippokratis Apostolidis, Panagiotis Stylianidis, Georgia Papantoniou and Thrasyvoulos Tsiatsos
Appl. Sci. 2021, 11(19), 8950; https://0-doi-org.brum.beds.ac.uk/10.3390/app11198950 - 26 Sep 2021
Cited by 1 | Viewed by 1684
Abstract
The presented paper examines the students’ adoption of the use of a cost-effective biofeedback system for anxiety awareness in parallel to examination activities. Human anxiety is classified by evaluating bio-signals related to skin conductance, skin temperature and heart rate. The participants of the [...] Read more.
The presented paper examines the students’ adoption of the use of a cost-effective biofeedback system for anxiety awareness in parallel to examination activities. Human anxiety is classified by evaluating bio-signals related to skin conductance, skin temperature and heart rate. The participants of the research were 44 students who were taking examinations in the form of synchronous online tests in the classroom for one of their courses. At first, the usability of the biofeedback system was examined using the system usability scale (SUS). The statistical analysis indicated that the examined system usability is quite satisfactory. Then, the study attempted to investigate the relationships between the students’ technology readiness personality dimensions, perceptions of usability, and the usefulness of the presented system by exploiting the technology readiness and acceptance model (TRAM). The results showed that the students’ optimism and attitude towards using the system are significant factors that affect the model’s relationships. The examined relationships are presented via a path model. Full article
(This article belongs to the Special Issue ICT and Statistics in Education)
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