Educational Technology Research and Development最新文献

With continued growth in online learning, motivation remains a key factor in persistence and achievement. Online mathematics students struggle with self-regulation and self-efficacy. As reported by Ryan and Deci (Self-determination theory: basic psychological needs in motivation, development, and wellness, Guilford Press, 2017, https://doi.org/10.3233/EFI-2004-22201), in their well-established self-determination theory, contended that satisfying the psychological needs of autonomy (involving self-regulation), competence (involving self-efficacy), and relatedness (involving a sense of belonging) creates a suitable environment for integrated extrinsic and intrinsic motivation to thrive. The purpose of this action research was to implement a self-determination theory-based online unit for mathematics students to improve their motivation levels. A convergent mixed methods action research design was employed to identify changes in the levels of autonomy, competence, and relatedness of the participants in an Algebra 2 course (n = 50) at a fully online school in the northeastern United States. Results from the motivation questionnaire and student interviews indicated a significant increase in competence and relatedness after completing the intervention. While no significant increase in autonomy was evident in the quantitative results, the qualitative findings showed some support for improved autonomy. Recommendations for online mathematics course design to support increased motivation are provided.

A chatbot is artificial intelligence software that converses with a user in natural language. It can be instrumental in mitigating teaching workloads by coaching or answering student inquiries. To understand student-chatbot interactions, this study is engineered to optimize student learning experience and instructional design. In this study, we developed a chatbot that supplemented disciplinary writing instructions to enhance peer reviewer’s feedback on draft essays. With 23 participants from a lower-division post-secondary education course, we delved into characteristics of student-chatbot interactions. Our analysis revealed students were often overconfident about their learning and comprehension. Drawing on these findings, we propose a new methodology to identify where improvements can be made in conversation patterns in educational chatbots. These guidelines include analyzing interaction pattern logs to progressively redesign chatbot scripts that improve discussions and optimize learning. We describe new methodology providing valuable insights for designing more effective instructional chatbots by enhancing and engaging student learning experiences through improved peer feedback.

Inquiry-based instruction has played an important role in science education, and been recognized as a critical approach to improve students’ scientific learning effectiveness. However, current research revealed that it is a challenge for teacher education programs to improve pre-service science teachers’ inquiry-based instructional activity design competency. Due to the dynamic and complicated process of the instructional design competency improvement, there is a strong need for new methods that could trace this process. Considering the Knowledge Integration (KI) theory has been demonstrated to be able to help science teachers design their inquiry-based instructional activities in a large amount of existing research, in this study, a KI-based collaborative learning environment was designed to support 19 pre-service science teachers’ inquiry-based instructional activity design. Epistemic network analysis (ENA) was applied to trace the development process of their inquiry-based instructional activity design e behaviour patterns. Data analysis results revealed that the pre-service science teachers demonstrated gradually more active in “guiding students to design exploratory activities” and “guiding students to communicate and cooperate” in their instructional designs during the process of using the KI-based collaborative learning environment. Through identifying and comparing the design patterns of the high-performing and low-performing groups, the results showed that the low-performing groups demonstrated more active on “posing inquiry questions” and “guiding students to formulate scientific explanation,” while the high performing groups demonstrated more active in “guiding students to design exploratory activities” and “guiding students to communicate and cooperate.” Furthermore, the semi-structured interview results demonstrated that the KI-based collaborative learning environment not only provided the pre-service science teachers a convenient way on online collaboration, but also helped them form more normative and integrated understandings on inquiry-based instruction. However, this study demonstrated that quite a few pre-service science teachers still had misconceptions on inquiry-based instruction. Suggestions are provided for improving pre-service science teachers’ inquiry-based instructional design competency in a technology-enhanced learning environment.

Two questions regarding text signals’ influence on second language (L2) science expository text comprehension were examined. First, the contextual relationship between verbal headings and non-verbal underlining signals (i.e., related or unrelated) was manipulated to investigate how these verbal and nonverbal text signals influence L2 text comprehension. Second, the physical distance between a heading and the underlined terms (i.e., close or distant) was manipulated to investigate how the physical proximity to the heading influences L2 text comprehension. University mixed proficiency Korean English language learners (n = 160) were randomly assigned to one of four conditions by proficiency level in a 2 (related or unrelated) × 2 (close or distant) design; one coherent text and three incoherent texts. Then all participants read assigned multiple-topic expository text, created a visual map of the text they read, and then completed a comprehension posttest (all in English). For the low proficient L2 readers, a heading served primarily as a general visual cue, leading the readers to respond only to underlined information regardless of the relatedness of heading and distance. For the high proficient L2 readers, a heading acted as a content-specific cue leading the readers to respond more to underlined information that related to the heading content and heading closeness. These results have direct instructional text design implications for organizing L2 expository texts for L2 readers.

In formal educational settings, such as online university lectures, instructional videos often consist of PowerPoint slides accompanied by a video or audio explanation from the instructor. It has been assumed that the social cues provided by the instructor’s video may facilitate affective processes and affect learning outcomes. Research on instructor presence in instructional videos has focused primarily on laboratory and online studies that are not embedded in the courses in which learners are enrolled. Therefore, we present three field studies examining instructor presence in instructional videos embedded in higher education courses to strengthen external validity (exam-relevant topic, > 30 min long, personally known instructor). The results of these studies show positive effects of a visible instructor compared to no visible instructor on some affective measures: social presence in Study 1 (n = 18, d = .85) and well-being in Study 3 (n = 38, d = 1.01), but not on others (well-being in Studies 1 & 2 (n = 53); motivation in Studies 1–3, social presence in Studies 2 & 3). They also show no effects on extraneous processing or learning outcomes (Studies 1–3). Thus, no general effect of instructor presence can be shown for instructional videos embedded in university courses in higher education, but there are also no detrimental effects. This leads to implications for future research, teaching, and design practice.

Computational thinking is acknowledged as an essential competency for everyone to learn. However, teachers find it challenging to implement the existing learning approaches in K-12 settings because the existing approaches often focus on teaching computing concepts and skills (i.e., programming skills) rather than on helping students develop their computational thinking competency—a competency that can be used across disciplinary boundaries in accordance with curriculum requirements. To address this need, the current study investigated how game-based learning influenced middle school students’ learning processes, particularly on the development of computational thinking competency, self-efficacy toward computational thinking, and engagement during gameplay. Additionally, the study examined how these outcomes were moderated by individual differences. We observed evidence that the gaming experience influenced students’ computational thinking self-efficacy, but not computational thinking competency or game-based engagement. Compared to age (grade) and prior gaming experience, gender tended to play a more important role in moderating students’ computational thinking competency, self-efficacy toward computational thinking competency, and game-based engagement. Implications and possible directions for future research regarding using game-based learning to enhance computational thinking competency are discussed.

Although the metaverse is a trending topic in several fields, it is not a new concept within the field of education. In this study, we followed the PRISMA framework and identified 37 articles since 2008 that researched the metaverse in education. We critically reviewed these articles, aiming to examine the evolution of the field’s conceptual understanding of the metaverse in education, identify its applications and effects, as well as synthesize the technical solutions and adoption challenges for implementing metaverse systems in schools. We found that the early empirical implementation of metaverse concepts in education mainly emphasized the characteristics of 3D virtual environments and avatars using the Second Life and OpenSim platforms. These traditional applications were found to be effective in supporting various teaching methods and enhancing students’ learning experiences and outcomes. In recent studies, more advanced technologies that pursue the fusion of physical and virtual environments (e.g. AI techniques, VR/AR devices, cloud platforms, wearable devices) have been incorporated into metaverse systems. However, the extent to which physical and virtual environments were fused in metaverse applications in education needs to be further clarified. We suggest that the conceptual clarity of the metaverse in education will keep evolving along with the technology development, and teacher preparedness for this new technical revolution needs more attention.

A majority of research in Computational Thinking (CT) mainly focuses on teaching coding to school students. However, CT involves more than just coding and includes other skills like algorithmic thinking. The current study developed an Online Inquiry-based Learning Platform for Computational Thinking (CT-ONLINQ) that follows Inquiry-Based Learning (IBL) pedagogy to support CT activities. IBL-based CT steps include algorithm design, analysis, and comparison of algorithms. Also, the platform allows students to explore multiple solutions to a problem and provides multiple-try feedback with hints as support during problem-solving activities. The hint generation strategy uses a Knowledge Graph that captures knowledge about the problem's solution in a machine-processible form. A six-week quasi-experimental study was conducted to determine the effectiveness of multiple-try feedback with hints on students’ CT skills. The study included 79 high school students: 41 students as part of the experimental group (EG) were provided problem-specific hints, and 38 as part of the control group (CG) with CT-general hints. The results showed that the students in the EG group improved their CT skills significantly more than those in the CG group. In addition, the study also evaluates the effectiveness of intervention considering biases in gender and prior coding experience. Female students performed better than male students in both groups after the intervention. Furthermore, in EG group, observations showed that students without coding experience performed better than their counterparts with experience. The findings suggest that the IBL-based CT activity on CT-ONLINQ can be deployed to improve the CT skills of school students.