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Technology Enhanced Science Education: Research Innovations in Pedagogy and Practices

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Education and Approaches".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 14457

Special Issue Editors

Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong SAR, China
Interests: ICT-supported science education; AI in education; mobile learning; technology-oriented STEM education; higher-order thinking in interdisciplinary education
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Institute of Education, Nanyang Technological University (NTU), Singapore 639798, Singapore
Interests: computer-supported collaborative learning; mobile learning; computational thinking; seamless learning; interdisciplinary research
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Guest Editor
Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei 106, Taiwan
Interests: computer-assisted learning; mobile learning; personalized learning
Special Issues, Collections and Topics in MDPI journals
School of Educational Information Technology, Central China Normal University, Wuhan 430079, China
Interests: learning science; knowledge creation; advanced ability; STEM; learning assessment; computer-supported collaborative learning; learning analysis; metacognition
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of technologies and fast changes in the global environment, the roles of technologies in education are ever-changing. The effective integration of technology into the teaching and learning of science concepts and related skills is always one of the dominant areas of science education. From COVID-19 to post-COVID-19, the challenges, opportunities, and experiences of researchers, science educators, practitioners, and scholars in the research, pedagogy, and practices of science education should be very educational and unique, and thereby worth sharing. It is time for us to communicate these changing experiences with different stakeholders in the field of educational technology, science education, and learning sciences. Such communication and sharing are intended to motivate reflections on the progress of research in technology-enabled science education and provide new visions and clear directions for the future study of new pedagogies and practices. This Special Issue will address the pedagogical innovations of technology-enhanced learning and practices of integrating new/emerging technologies in science education in formal and informal learning contexts.

Topics of interest for this Special Issue include, but are not limited to, the following:

  1. Emerging technologies (i.e., AI, VR, AR) in science education;
  2. e-learning tools (i.e., mobile learning tools, learning management systems, assessment tools, simulations, scientific modelling tools) in science education;
  3. Pedagogical design and implementation of technology-enhanced science education;
  4. Coding education and computational thinking in science education;
  5. Computer-supported collaboration in science education;
  6. Mobile technology-supported science education;
  7. Technology-supported science learning in blended learning contexts;
  8. Technology-supported science learning informal contexts.

You may choose our Joint Special Issue in Education Sciences.

Dr. Daner Sun
Prof. Dr. Chee Kit Looi
Prof. Dr. Ting-Chia Hsu
Dr. Yuqin Yang
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. Sustainability 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

  • emerging technologies (i.e., AI, VR, AR)
  • science education
  • e-learning tools
  • pedagogy
  • coding education
  • computational thinking
  • model learning
  • CSCL
  • informal learning contexts
  • blended learning

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Published Papers (3 papers)

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Research

21 pages, 1627 KiB  
Article
Examining Pre-Service Chemistry Teachers’ Technological Pedagogical Content Knowledge (TPACK) of Using Data-Logging in the Chemistry Classroom
by Feng Deng, Wanrong Lan, Daner Sun and Zhizi Zheng
Sustainability 2023, 15(21), 15441; https://doi.org/10.3390/su152115441 - 30 Oct 2023
Viewed by 2085
Abstract
In recent decades, the integration of technology, particularly data logging, has become a cornerstone of effective science teaching, placing increased emphasis on the cultivation of teachers’ Technological Pedagogical Content Knowledge (TPACK). While the TPACK framework has garnered attention in science education, limited research [...] Read more.
In recent decades, the integration of technology, particularly data logging, has become a cornerstone of effective science teaching, placing increased emphasis on the cultivation of teachers’ Technological Pedagogical Content Knowledge (TPACK). While the TPACK framework has garnered attention in science education, limited research has explored the interplay of TPACK components within a constructivist context, particularly in the context of data-logging-supported chemistry class. To bridge this research gap, this study conducted a comprehensive survey on TPACK with 181 pre-service chemistry teachers, probing their TPACK as it pertains to data logging. Results from both exploratory and confirmatory factor analyses underscored the reliability and validity of the survey instrument. Subsequently, structural equation modeling was employed to illuminate the intricate relationships among various facets of TPACK. Findings suggested a sequential developmental pattern within TPACK, with teachers’ Technological Pedagogical Knowledge (TPK), Technological Content Knowledge (TCK), and Pedagogical Content Knowledge (PCK) all exerting a positive influence on their overall TPACK. Moreover, this study unveiled a significant correlation between pre-service chemistry teachers’ data-logging TPACK and their capacity for design thinking. Interestingly, gender differences in TPACK were negligible. In light of these findings, this study not only contributes to our understanding of TPACK development but also has practical implications for nurturing pre-service chemistry teachers’ proficiency in TPACK when using data-logging. Full article
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25 pages, 3257 KiB  
Article
Fostering AI Literacy in Elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) Education in the Age of Generative AI
by Stefanus Christian Relmasira, Yiu Chi Lai and Jonan Phillip Donaldson
Sustainability 2023, 15(18), 13595; https://doi.org/10.3390/su151813595 - 12 Sep 2023
Cited by 14 | Viewed by 6389
Abstract
The advancement of generative AI technologies underscores the need for AI literacy, particularly in Southeast Asia’s elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) education. This study explores the development of AI literacy principles for elementary students. Utilizing existing AI literacy models, a [...] Read more.
The advancement of generative AI technologies underscores the need for AI literacy, particularly in Southeast Asia’s elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) education. This study explores the development of AI literacy principles for elementary students. Utilizing existing AI literacy models, a three-session classroom intervention was implemented in an Indonesian school, grounded in constructivist, constructionist, and transformative learning theories. Through design-based research (DBR) and network analysis of reflection papers (n = 77), the intervention was evaluated and redesigned. Findings revealed clusters of interdependent elements of learner experiences, categorized into successes, struggles, and alignments with learning theories. These were translated into design moves for future intervention iterations, forming design principles for AI literacy development. The study contributes insights into optimizing the positive effects and minimizing the negative impacts of AI in education. Full article
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20 pages, 3988 KiB  
Article
Research on the Quality of Collaboration in Project-Based Learning Based on Group Awareness
by Rui Zhang, Ji Shi and Jianwei Zhang
Sustainability 2023, 15(15), 11901; https://doi.org/10.3390/su151511901 - 2 Aug 2023
Cited by 5 | Viewed by 5323
Abstract
Project-based learning (PBL) is an important form of collaborative learning that has a significant positive impact on student capacity development. However, data generated during long periods of PBL are difficult to record in real time, and there is a dearth of specific empirical [...] Read more.
Project-based learning (PBL) is an important form of collaborative learning that has a significant positive impact on student capacity development. However, data generated during long periods of PBL are difficult to record in real time, and there is a dearth of specific empirical research on the relationship between the quality of collaboration and the effectiveness of collaboration. In this study, we employ text mining to measure and analyze process data from a college physics course that utilizes project-based learning at a university. Under the group awareness theory, we construct a project-based learning system and extract six multi-dimensional awareness data (including numbers of text, cognitive awareness, emotional awareness, behavioral awareness, social awareness of group members, and group leaders’ cognitive awareness of the project). These data are then utilized to build a multiple regression model, which enables the analysis of collaboration quality within collaborative groups. The results show that the group awareness information automatically processed by text mining can reflect the quality of collaboration, and the quality of collaboration can determine about 50% of the effectiveness of collaboration. The important factors affecting the collaboration quality of project-based learning were group leaders’ cognitive awareness of the project and the cognitive awareness of group members. Therefore, in order to improve the quality of collaboration in PBL, teachers should select responsible group leaders and encourage meaningful communication between group members, thereby fostering high-quality and sustainable collaboration development. Full article
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