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Background: TPACK is a widely used framework for assessing teachers' competence in integrating technology in education. However, previous studies have shown varying interpretations of the relationship between TPACK elements. Qualitative studies that assess the manifestations of TPACK by examining the practices of pre‐service teachers are rare. Objectives: This study investigates technology integration in innovative physics teaching and learning materials designed by pre‐service teachers and the manifestation of technological pedagogical content knowledge (TPACK) in empirical cases. Methods: We qualitatively extracted the components of PCK, TPK, and TCK from the innovative physics teaching and learning materials developed by 22 pre‐service teachers in their fourth year at a teachers' college in South Korea. We scored them based on the new evaluation criteria established in this study. Results and Conclusions: Based on the materials, we identified three types of technology integration: Learning Materials Providing, Learning Activity Providing, and Virtual Experiments Creating. This study identifies teachers' level of TK and integrates it with TPACK expression. Results confirm the connection between TK and TCK and show that a strong PCK can serve as a basis for TPK. The TPACK expression pattern can help achieve balanced development of TPACK in teacher education. Lay Description: What is currently known about the subject matter: TPACK framework combines pedagogical, content, and technological knowledge in teachers' professional expertise.Despite TPACK's widespread use, studies showed varied interpretations of the relationships between its elements.TPACK measurement often relies on self‐assessment, lacking a total reflection of technology use in teaching.Few qualitative studies explore TPACK manifestations through pre‐service teachers' practices. What the paper adds to the currently known about: There are three types of technology integration: Learning Materials Providing, Learning Activity Providing, and Virtual Experiments Creating.The study found that pre‐service teachers in the virtual experiments creating type exhibit strong subject‐specific TPACK.In physics education, TK is essential and can be divided into the use of ICT and programming.The study correlates TK levels with TPACK expressions, resulting in five patterns based on PCK, TPK, TCK, and TK. The implications of study findings for practitioners: The study presents empirical evidence of TPACK manifestation in pre‐service physics teachers, focusing on TK.High programming TK has a significant impact on subject‐specific TPACK.The study confirms the TK‐TCK connection and highlights PCK's role in TPK.TPACK patterns can guide teacher education, fostering balanced development. [ABSTRACT FROM AUTHOR]

Background: The substantial growth in gamification research has connected gamified learning to enhanced engagement, improved performance, and greater motivation. Similar to gamification, personalized learning analytics dashboards can enhance student engagement. Objectives: This study explores the student experiences and academic achievements using a gamified dashboard in a large, introductory STEM course. Methods: We examined two groups of students enrolled in different sections of a one‐semester‐long physical geology course with a total enrollment of 223 students. The only difference between the groups was that one had access to the dashboard. The data collection included students' assignments, overall performances, and exam scores. Students in both sections completed a Science Literacy Concept Inventory survey at the beginning and end of the term. Additionally, students completed an end‐of‐term survey containing open‐ended questions on their experience and interactions with specific elements. Results: Students shared mostly positive comments about their experience with the dashboard, and the final grade of students with access to the dashboard was 13% higher, on average, compared to their peers in the non‐dashboard section. Conclusion: With low costs and little time invested, gamified dashboards could have a significant impact on student performance in large STEM lecture courses. Lay Description: What is already known about this topic: Leaner dashboards that provide personalized feedback are linked to improved student performance in undergraduate STEM courses. However, students may be reticent to adopt dashboards, especially students in the middle range of the performance distribution, for whom the impact of the dashboard may be most significant.Prior research on gamification in STEM courses suggests that adding gameful elements like progress trackers, badges, and rewards can increase students' engagement in undergraduate coursework.The combination of personalized learning in dashboards and the motivational experience of gamification should boost student engagement, dashboard adoption, and ultimately foster academic achievement. What this paper adds: In this paper, we examine the differences in academic performance between students with and without access to a gamified learning dashboard in an undergraduate Geology course.We observe that students with access to the dashboard (the treatment group), outperform students without access (the control group). The greatest benefit is observed for students who use the dashboard more frequently.Students reported that the progress tracker, the badges, and the rewards all incentivized their use and provided useful feedback about their performance. Students who did not adopt the dashboard expressed a need for more detail about the tool and its purpose. Implications for practice and/or policy: Instructors and instructional designers for large enrollment undergraduate STEM courses should consider the affordances of gamified learner dashboards for increasing engagement and for providing synchronous feedback about learners' strategies in the course.Aligning the dashboard to the content of the curriculum—by ensuring that badges reflect key concepts‐ encouraged participation and helped students identify the utility of the tool. Dashboards should be personalized to individuals and to the course.Adding gameful elements in a low‐cost intervention for increasing adoption and engagement of dashboards in large enrollment introductory courses. [ABSTRACT FROM AUTHOR]

Live streaming platforms like Twitch.tv count millions of viewers and performers, pointing to novel practices and interactions. Instructional applications of this phenomenon are rising with thematic channels and shows aimed at teaching and debating a variety of subjects ranging from art to programming. However, few research publications have specifically explored trends in pedagogical strategies and learning behaviours of viewing audiences. This study responded to this need by analysing computer science shows on Twitch.tv. A total of 40 hours of live streaming were analysed within a Community of Inquiry framework using the concepts of social affordances, computational thinking, and teaching style. Data collected from both expert and novice streamers included streamers' actions, on‐screen activity, and online discussions. Results pointed to specific tactics employed by both performers and viewers for exploring computer science issues and dynamics together, with instances of peer‐tutoring, construed learning, and significant transparency, even when top‐down instruction was staged. Practitioners notesWhat is already known about this topic Live streaming is a popular media practice all around the world, with Twitch.tv as the leading hosting platform.A rising number of live streaming shows are focusing on education and learning topics, from STEM to art.What this paper adds A first exploration of instructional streaming focused on computer science education.An analysis of best practices in instructional streaming in terms of community building, teaching style, and computational thinking processes.A better understanding of how communities of inquiry can be hosted on Twitch.tv.Implications for practice and/or policy Practitioners can harness this study's results for informing better educational streaming.Educators may refer to this article's highlights for selecting and evaluating educational streaming shows.Policy makers will be able to use this article's insights for monitoring and re‐applying effective computer science activities in other educational environments. [ABSTRACT FROM AUTHOR]

Background: Educational robotics (ER) is a means of teaching technology and engineering to students that offers an active learning environment by encouraging them to create meaningful and unique products. ER also gives students the opportunity to work collaboratively. Objectives: In this study, elementary school students' behavioral patterns were explored while they were working on a collaborative robotics project. Additionally, behavioral patterns of higher‐achievement and lower‐achievement groups were compared. Methods: The participants of the study were a total of 18 students (aged 10–12), including 17 males and 1 female. A problem‐based robotics competition was designed within the scope of the study. The students were asked to design and program a robot based on certain rules in groups within four weeks for this competition. All robot design processes and the competition were video‐recorded. Quantitative content analysis and lag‐sequential analysis methods were used to analyze students' behaviors. Results and Conclusions: The results showed that ER improves collaborative learning, and behaviors in the contributing and planning categories were the dominant behaviors during the robotics project development. Grouping skills of higher‐achievement groups were better. Based on the significant collaborative behavioral patterns that emerged from the study, implications were discussed in terms of theoretical insights and collaborative educational robotics practices. Lay Description: What is already known about this topic: Studies have shown that educational robotics (ER) has a potential impact on students' collaborative learning (CL).Communication and collaboration skills stand out among the 21st century skills that students need to have.Knowledge‐construction behaviours are very important in CL, and researchers have conducted studies to determine behavioural patterns in different technological environments.Previous studies have highlighted the importance of understanding students' behavioural patterns in technology‐assisted learning environments. What this paper adds: This study aims at comprehensively examining collaborative behavioural patterns of elementary school students working on a robotics project.The results showed that behaviours in the contributing and planning categories were the dominant behaviours.Grouping skills of higher achievement groups were better. Implications for practice and/or policy: Our results suggest that ER activities can improve students' co‐regulation skills by supporting the problem‐solving process.ER could be considered as a tool able to contribute to collaborative learning.By using problem‐based collaborative educational robotic activities, students' interactions with their peers can be strengthened.Students' grouping skills should be taken into consideration when establishing groups in ER activities. [ABSTRACT FROM AUTHOR]

This paper reports on a study aiming at examining the effect of the digital storytelling approach on the aggregate reasoning of high school students. A pretest-posttest quasi-experimental design was implemented on 50 10th-grade students for five weeks to reveal the effectiveness of digital storytelling in mathematics courses regarding aggregate reasoning. Results of statistical analysis showed a significant improvement in aggregate reasoning in favor of the students in the digital storytelling group. It was also noted that aggregate reasoning was specifically enhanced to analyze data and interpret results rather than the other two components (formulate question and collect data) in the experimental group. The results support the idea that the use of digital storytelling can be an effective instructional tool for statistics education and provide implications for course designers to provide better teaching of aggregate reasoning. • Aggregate reasoning is an essential skill at the core of statistical reasoning. • Aggregate reasoning is involved in every component of the statistical process. • DST, effective to construct context is essential in statistics education. • DST improves aggregate reasoning, especially data analyze, and interpret results. [ABSTRACT FROM AUTHOR]

Creativity is widely described as a key '21st Century skill'. Science education in schools has emphasized the development of science inquiry and problem-solving skills with the support of technology, and paid insufficient attention to creative thinking skills for producing innovative ideas or solutions. This paper presents an exploratory study aiming to investigate how secondary school students engage in scientific creativity tasks with the support of technology, in particular how they generate ideas in small groups via applying relevant thinking strategies, engaging in social communication, and constructing a computer-based mind map to facilitate group thinking. The participants were 24 Grade 11 students from a high school, who worked on a set of scientific creativity tasks in 6 groups. Epistemic network analysis of group conversations reveals that constructing a mind map helped students to retain ideas for elaboration and evaluation, stimulate new threads of discussion, and regulate task progression. Compared to low-performing groups, high-performing groups engaged more in divergent thinking, mind mapping, and regulative discussions, in addition to making these activities more closely connected with idea generation. These findings have implications for the design of technology-supported educational interventions intended to promote and improve group creativity in science education. • We investigate how students generate ideas together via computer-based mind mapping. • Mind mapping helps retain thoughts, stimulate new ideas, and regulate discussions. • High-performing groups engaged more in thinking, mapping, and regulative discussions. • Mapping, thinking, and idea generation are more connected in productive discourse. [ABSTRACT FROM AUTHOR]