Technologically Enhanced Teaching Practices That Engage Student Learning

A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Technology Enhanced Education".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 2910

Special Issue Editors


E-Mail Website
Guest Editor
School of Information and Communication Technology, University of Tasmania, Hobart 7007, Australia
Interests: educational technology; learning analytics; cybersecurity
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Information and Communication Technology, University of Tasmania, Hobart 7007, Australia
Interests: ICT curriculum design and development; ICT industry placements within curriculum; student engagement and retention

E-Mail Website
Guest Editor
Information & Communication Technology, University of Tasmania, Hobart, Australia
Interests: ICT in education; information and communication technology; e-learning; technology enhanced learning; computers in education; online learning; online education; e-learning in higher education; blended learning; teaching and learning

E-Mail Website
Guest Editor
Pattern Recognition Lab, Chonnam National University, Gwangju, Republic of Korea
Interests: deep-learning-based emotion recognition; medical image analysis; pattern recognition
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

1) The issue introduction includes the background and the importance of this research area.

Teaching and learning in tertiary education has become more online dependent. Although online learning and teaching has a long history, it has flourished recently due to technological advancements as well as environmental demands such as COVID-19. At the same time, technology can enhance learning in a variety of other ways. Technology can support student-centered learning by providing connections between peers, staff, and resources, and making learning more engaging and accessible. Technology can assist academics with assessment, detecting plagiarism, and automated feedback. Learning management systems provide large datasets that, with the aid of learning analytics, enable a deeper understanding of how students interact with the system as well as with their peers.

2) The aim and scope of the Special Issue shall be highlighted.

This issue focuses on how technology enhances teaching and learning in tertiary education.

3) Suggested themes shall be listed.

In particular, this Special issue encourages submissions on the following topics: (1) online learning design; (2) project-based learning; (3) inclusive learning engagement in online learning; (4) technology-enhanced learning; (5) AI or deep-learning techniques applied based on interactive data including emotion; (6) learning analytics.

Dr. Soonja Yeom
Dr. Nicole Herbert
Dr. Matthew Springer
Prof. Dr. Soo-Hyung Kim
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 double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Education Sciences is an international peer-reviewed open access monthly 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 1800 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

  • educational technology
  • learning analytics
  • retention
  • engagement
  • technology-enhanced learning
  • emotion and learning
  • applied AI techniques in learning
  • emotion detection from students’ comments (interaction with LMS)

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

25 pages, 478 KiB  
Article
Closing the Gap? The Ability of Adaptive Learning Courseware to Close Outcome Gaps in Principles of Microeconomics
by Karen Gebhardt and Christopher D. Blake
Educ. Sci. 2024, 14(9), 1025; https://doi.org/10.3390/educsci14091025 - 19 Sep 2024
Abstract
Research shows that students who identify as low-income, first-generation, and/or racially diverse disproportionately underperform in college and earn fewer degrees than other students. This study explores the integration of adaptive learning courseware assignments as a tool to help close these outcome gaps and [...] Read more.
Research shows that students who identify as low-income, first-generation, and/or racially diverse disproportionately underperform in college and earn fewer degrees than other students. This study explores the integration of adaptive learning courseware assignments as a tool to help close these outcome gaps and to ensure more equitable learning across diverse student groups. Adaptive learning courseware is an educational technology that requires students to master the same learning objectives but, for each student, the courseware determines the order and timing of content based on how that student interacts with the courseware, thus enabling an individualized learning path for each student. Adaptive learning assignments were implemented in five sections of a highly-enrolled Principles of Microeconomics course at a medium-sized state university in the United States. This study draws from student data (n=581), which includes adaptive learning assignment completion data, detailed exam and final grade data, and institutional demographic data. Descriptive statistics and regression analyses are used to explore if the completion of adaptive learning assignments disproportionately benefited low-income, first-generation, or racially diverse students, thus helping close the gap between students from different backgrounds. Findings include significant evidence that adaptive learning assignment completion was correlated with more exam questions answered correctly by all students, with this correlation being disproportionately stronger for students who identify as being from a minority background and for foundational (easy) exam questions. Full article
Show Figures

Figure 1

26 pages, 1667 KiB  
Article
Enhancing ICT Literacy and Achievement: A TPACK-Based Blended Learning Model for Thai Business Administration Students
by Cherisa Nantha, Kobchai Siripongdee, Surapong Siripongdee, Paitoon Pimdee, Thiyaporn Kantathanawat and Kanitphan Boonsomchuae
Educ. Sci. 2024, 14(5), 455; https://doi.org/10.3390/educsci14050455 - 25 Apr 2024
Cited by 2 | Viewed by 1330
Abstract
The COVID-19 pandemic has heightened the need for 21st century skills, particularly computer and ICT literacy (CICT) in Thailand. This study aimed to develop a TPACK (Technological Pedagogical and Content Knowledge)-based blended learning model (BLM) to enhance CICT skills and academic performance among [...] Read more.
The COVID-19 pandemic has heightened the need for 21st century skills, particularly computer and ICT literacy (CICT) in Thailand. This study aimed to develop a TPACK (Technological Pedagogical and Content Knowledge)-based blended learning model (BLM) to enhance CICT skills and academic performance among 179 Business Administration (BA) undergraduates in the 2022 academic year Computer and Information Applications course. Research instruments were designed and evaluated by experts. Over 18 weeks, qualitative and quantitative data were collected, with the qualitative data undergoing content analysis. Descriptive statistics were used to analyze quantitative data, comparing pretests, post-tests, and 2-week retests using a repeated measure ANOVA. One-sample t-tests were used to assess the model’s impact on CICT skills. The results showed a significant score improvement between tests, with the highest mean being seen in the 2-week retest. The BA-TPACK model significantly enhanced CICT skills, exceeding 80%. The students expressed high satisfaction, with the BA-TPACK model effectively enhancing CICT skills and academic achievement, recommending its integration into future computer and information courses. This study’s contribution lies in addressing the pressing need for CICT skills in the ‘new normal’. By developing and implementing a BLM grounded in the TPACK framework, this study not only enhances students’ CICT proficiency but also fills a crucial gap in the literature regarding effective pedagogical approaches to foster 21st century skills. Full article
Show Figures

Figure 1

Back to TopTop