Computers & Education最新文献

Video learning is a crucial component in flipped learning related to learners' readiness to attend more complex face-to-face activities. However, instructors may not know students' preparedness and motivation for each class. This study intended to examine the underlying mechanism between students' before-class video-viewing engagement and performance. We investigated learners' motivation (i.e., autonomous and controlled motivation) based on self-determination theory and controlled for their gender, age, and prior performance. An integrated temporal model was built under the dynamic structural equation modeling framework. Participants were 118 Taiwanese graduate students (78 females and 40 males) with a mean age of 26.14 years old. Study findings showed that students engage with the video content in a consistent viewing pattern, which has a significant relationship with their motivation and academic performance from week to week. The frequency of skipping backward was negatively associated with controlled motivation, while the frequency of pauses was positively associated with autonomous and controlled motivation. A high frequency of skipping forward predicted lower learning performance. Besides, a higher ratio of skipping backward predicted higher controlled motivation. Male students, older students, and students with higher prior performance exhibited higher autonomous motivation, which was related to better learning performance. Understanding these relationships can help educators and instructional designers develop more effective strategies for fostering students’ preparedness, engagement and success in active learning contexts. The study findings were discussed considering theoretical advancement and practical implications for enhancing personalized and active learning in higher education to achieve educational equity.

Open Educational Resources (OER) repositories provide teachers with a wide range of learning resources (LRs), enabling them to design various learning sequences. However, search & select in large OER repositories can be a daunting task for teachers. Incorporating peer recommendations, as is common in online marketplaces, is becoming a popular solution that seeks to exploit the wisdom of the crowd for this task. However, teachers are often reluctant to take a contributory role and provide social recommendations. In addition, little is known about the actual value of social recommendations as a search aid. In this research, we implemented a “light-weight” socially-based recommender system (RS) within a large OER repository that includes social network features. We examined two aspects of the socially-based recommendation mechanisms. First, their utility as search aids that assist teachers in searching and selecting suitable LRs, and second, their impact on teachers' incentives to share recommendations that can assist fellow teachers. To study these two aspects, we examined two science teacher communities using this repository. The results demonstrated the incentivising power of social rewards, and the value of social recommendations as means for search & select. However, we also observed a heterogeneous effect of social features on teachers' behaviour. To explore the factors that may explain these differences, we employed a mixed-method approach, combining qualitative, quantitative, and Social Network Analysis methods. Triangulation of the findings underline the relation between the strength of the social ties within the teachers’ community and the effectiveness of socially-based features.

Critical thinking, Communication, Collaboration, and Creativity are regarded as key skills for today's learners. Interest in robotics usage to develop such competencies in educational settings arises but there hasn't been so far mapping of the research conducted in this field. Thus, we present a scoping review of 59 articles published from 2012 to 2023 in 4 Databases and 2 Registers examining kindergarteners' skills through Educational Robotics. Our goal was to map which skills are commonly examined in kindergarten and under which terminology as well as to investigate the studies' features, the types of robotics, and the assessment tools utilized. Our findings depict that several skills are evaluated using different terms. Critical thinking is examined most frequently, creativity the least, and communication is integrated into collaboration and the opposite. Most of the researchers used the mixed method focusing on qualitative tools, examining quite a small sample size, and conducting the intervention for a short time. Also: BeeBot, Lego robotics kits (WeDo, Mindstorms), and social, humanoid robots are often used. Additionally, the evaluation tools used in the reviewed papers are presented and categorized into groups. This scoping demonstrates that robotics might affect positively the children's cognitive skills and creativity but may not facilitate their interactions so much regarding emotional expressions. Moreover, a gap in quantitative research on kindergarteners' skills development via Educational Robotics is spotted. Finally, this scoping review suggests: creating clear terms for skills, developing robotics tailored to kindergarten age, forming full robotics activities, and designing modular evaluation tools for young learners' capacities.

AI-powered learning technologies are increasingly being used to automate and scaffold learning activities (e.g., personalised reminders for completing tasks, automated real-time feedback for improving writing, or recommendations for when and what to study). While the prevailing view is that these technologies generally have a positive effect on student learning, their impact on students’ agency and ability to self-regulate their learning is under-explored. Do students learn from the regular, detailed and personalised feedback provided by AI systems, and will they continue to exhibit similar behaviour in the absence of assistance? Or do they instead continue to rely on AI assistance without learning from it? To contribute to filling this research gap, we conducted a randomised controlled experiment that explored the impact of AI assistance on student agency in the context of peer feedback. With 1625 students across 10 courses, an experiment was conducted using peer review. During the initial four-week period, students were guided by AI features that utilised techniques such as rule-based suggestion detection, semantic similarity, and comparison with previous comments made by the reviewer to enhance their submissions if the feedback provided was deemed insufficiently detailed or general in nature. Over the following four weeks, students were divided into four different groups: control (AI) received prompts, (NR) received no prompts, (SR) received self-monitoring checklists in place of AI prompts, and (SAI) had access to both AI prompts and self-monitoring checklists. Results of the experiment suggest that students tended to rely on rather than learn from AI assistance. If AI assistance was removed, self-regulated strategies could help fill the gap but were not as effective as AI assistance. Results also showed that hybrid human-AI approaches that complement AI assistance with self-regulated strategies (SAI) were not more effective than AI assistance on its own. We conclude by discussing the broader benefits, challenges and implications of relying on AI assistance in relation to student agency in a world where we learn, live and work with AI.

Over the past decade, there has been an enormous upsurge in the use of educational apps in primary schools. However, few studies have examined how children interact with these apps and how their interaction patterns relate to learning outcomes. An interaction pattern that is potentially detrimental to learning is repeated mistakes, defined as making the same mistake more than once when answering a task. With interaction data from an eight-week digital vocabulary intervention, we examined 1) whether the propensity to make repeated mistakes changes across app sessions, and 2) how repeated mistakes relate to children's prior knowledge and their learning gains from the intervention. Our sample consisted of 363 Norwegian second graders who worked with the vocabulary app in a randomized controlled trial. Using growth curve modeling and confirmatory factor analyses, we found that the propensity to repeat mistakes remained stable over time. Furthermore, a structural equation model showed that repeated mistakes related negatively to both pre-test and post-test scores. A substantial proportion of the total effect of prior knowledge on learning gains was mediated by the propensity to repeat mistakes. Children who made more repeated mistakes had lower expected learning gains across all levels of prior knowledge. We suggest that the propensity to repeat mistakes may pose a double threat to learning by diminishing exposure to relevant content, and amplifying the exposure to incorrect input. Considering the stability of mistake repetition, it is crucial to identify students with a high propensity to repeat mistakes and help them break the pattern to support learning. App developers can help this process by implementing automatic detection and feedback.

This study explored the effects of out-of-class interactions with intelligent personal assistants (IPAs) versus human interlocutors on EFL learners' willingness to communicate (WTC) in English. A total of 92 first-year college students were recruited to participate in interactive out-of-class activities, which were held in 10-min sessions twice a week for 12 weeks. The participants were divided into three groups: an IPA group, who interacted with Alexa or Google Assistant through a smartphone; an EL1 group, who interacted with L1 English speakers; and an EL2 group, who interacted with L2 English speakers. WTC questionnaires and focus-group interviews were used to evaluate WTC. Significant differences in WTC were discovered between the three groups. The IPA group had greater WTC than did the EL1 or EL2 group. The intergroup differences were attributable to the interaction of contextual (interlocutor and time), individual (L2 self-confidence, anxiety, and proficiency), and sociopolitical (Taiwan's K-12 education) factors. The participants in the IPA group emphasized that the mobility, convenience, interactivity, multifunctionality, and familiarity of IPAs on smartphones enabled them to practice speaking English anywhere, anytime, and at their own pace. IPAs, as supportive and patient learning partners, enhanced the learners' engagement, confidence, and thus WTC.

One discussion in the context of education for sustainable development centres on the importance of cognitive as well as affective processes for promoting pro-environmental behaviour. In our study, we investigate how affordances of immersive Virtual Reality (iVR) such as the virtual embodiment of a tree might provide new opportunities to achieve this goal. The aim of our study was twofold: Firstly, we investigated whether multisensory enhancement of iVR has an additional, supporting effect on mechanisms that are vital to fostering nature connectedness and pro-environmental behaviour compared to non-enhanced iVR. Secondly, we examined the relationships between mediating variables to explain the underlying mechanisms of how nature connectedness and pro-environmental behaviour can be promoted through iVR. In our experimental design (N = 82), we tested the effects of multisensory enhancement of embodying nature in immersive Virtual Reality (iVR) compared to non-enhanced iVR on the processes considered vital to promoting pro-environmental behaviour: a) embodiment, b) perspective-taking, c) reflection on the relationship between oneself and nature, and d) connectedness to nature. According to self-reported measures, participants developed a feeling of embodiment and were able to change their perspective by stepping into the tree's point of view. Users also succeeded in situating the tree's experience into the greater context, often reflecting on the role of humankind towards nature. However, we found that multisensory iVR does not lead to an additional increase in nature connectedness, but is associated with a higher level of taking action and slightly more reflective processes. We propose a preliminary path-model that summarises the observed findings. Our results contribute to the small but growing body of research that evidences the effects of taking the perspective of non-sentient beings through iVR on nature connectedness and pro-environmental behaviour.

Scholars and practitioners have called for personalized and widely accessible professional development (PD) for teachers. Yet, a long-standing tension between customizing support and increasing access to such support has hindered the scale-up of high-quality PD for individual teachers. This study addresses this challenge by developing a computerized program for middle school mathematics teachers that provides frequent opportunities for teachers to interact with and obtain personalized and real-time feedback from a virtual facilitator based on natural language processing. Based on the data collected from 1727 middle school students in an experiment in which the teachers of these students were randomly assigned to the program or the business-as-usual condition (i.e., the control group), we found that the program had a statistically significant impact on students’ mathematics performance. These results demonstrate the potential of incorporating an automated, interactive feedback tool supported by artificial intelligence to create effective, scalable teacher PD.

Computational thinking is widely recognized as an essential skill for adapting to the current era, with programming learning being the most effective means to develop it. It is recommended that computational thinking and learning programming be introduced as early as elementary school. However, elementary school students often possess limited prior knowledge of programming, posing challenges in their learning process. The graphic organizers (GOs) may serve as a bridge between students’ existing knowledge and new learning, facilitating a deeper processing of the overall information and thereby enhancing the learning process. This can be particularly advantageous for early-stage learners when grappling with difficult subjects. Consequently, this study employed GOs to assist elementary school students in their computational thinking and programming learning, employing a quasi-experiment design to evaluate their effectiveness. The results showed that although all students demonstrated awareness of applying computational thinking to solve problems, those exposed to GO-based instruction exhibited higher levels of computational thinking, programming skills, and flow experiences.

In this paper, we review and meta-analyze the findings of experimental studies published between 2006 and 2022 that examined the effects of coding and programming interventions on children's core and higher order executive functions (response inhibition, working memory, cognitive flexibility, planning and problem solving). The systematic review and meta-analysis aimed to address three research questions: 1) Which executive functions are most impacted by the teaching of CT? 2) Which instructional modality (educational robotics/virtual coding/unplugged coding) is most effective in enhancing executive function skills in learners aged 4–16 years? and 3) Does the cognitive effectiveness of coding vary with children's age? A total of 19 studies with 1523 participants met the selection criteria for the systematic review. The meta-analysis included 11 of those studies. The results reveal beneficial effects of structured virtual and tangible coding (educational robotics) activities for preschoolers and first graders, and significant effects of more unstructured virtual coding activities (e.g., Scratch-based) for older students. A multivariate fixed-effects model meta-analysis shows that the teaching of coding significantly improves problem-solving with the highest effect (d_ppc2 = 0.89), but also planning (d_ppc2 = 0.36), and inhibition and working memory with lower effects (d_ppc2 = 0.17, d_ppc2 = 0.20).