Lessons Learned and Future Directions of MetaTutor: Leveraging Multichannel Data to Scaffold Self-Regulated Learning With an Intelligent Tutoring System

Measuring the Complexity of Self-Regulated Learning and Academic Challenges for Adolescents in Canada

Research that uses self-report measures to examine the complexity of self-regulated learning (SRL) and academic challenges for adolescents is limited. This study examined the psychometric property of the Self-Regulated Learning Profile and Self-Diagnostic (SRL-PSD) instrument and addressed the multi-components of SRL and academic challenges for adolescents. Participants were 358 adolescents from a Canadian middle school. The subscales of SRL-PSD were administered to students through LimeSurvey during a 25-min instructional session over two days. Results demonstrated the SRL-PSD was a reliable and valid self-report instrument to measure adolescents' SRL practices and academic challenges. Also, all types of SRL practices and academic challenges were significantly intercorrelated. Additionally, all types of SRL practices were positively associated with school engagement, whereas all types of academic challenges were negatively associated with school engagement. Overall, this study provides a validated self-report measure for educators and researchers to examine adolescents' SRL practices and academic challenges.

Multimodal measurements enhance insights into emotional responses to immediate feedback

Adaptive learning technologies often provide students with immediate feedback on task performance. This feedback can elicit various emotional responses, which, in turn, influence learning. Most recent studies capture these emotions by single data streams, contradicting the multi-componential nature of emotion. Therefore, this study investigated 32 university students solving mathematical problems using an adaptive learning technology. Students received immediate feedback on every step in the solution process, after which their physiological, experiential and behavioral responses to this feedback were recorded. Physiological arousal was measured by electrodermal activity, valence was measured by self-reports (experiential), and emotion types were measured by observations of facial expressions (behavioral). Results showed more peaks in electrodermal activity after feedback than was expected based on chance. These responses were comparable in strength after feedback on failure and success. Students' experiential responses conveyed mostly positive valence after feedback on success and mostly negative valence after feedback on failure. Behavioral observations showed more negative than positive emotion types after feedback on failure and more positive than negative emotion types after feedback on success. These results show that physiological arousal is a valuable objective indicator of emotional responses after immediate feedback but should be accompanied by other data streams in order to understand students' emotional responses. Both valence and emotion types can be used for this purpose. These outcomes pave the way for designing adaptive learning technologies that take students' emotions into account.

Harnessing the benefits of ChatGPT for radiography education: A discussion paper

OBJECTIVE

Radiography education is pivotal in training skilled radiographers for diagnostic imaging and therapeutic applications. With technological advancements, interest in innovative educational tools to enhance traditional teaching methods is growing. This discussion paper explores the possibility of the integration of ChatGPT, a cutting-edge conversational AI language model, into radiography education.

KEY FINDINGS

We report that ChatGPT offers interactive learning opportunities that can facilitate learning. It also provides self-paced learning, revision platforms, and supports educators in scenario creation, assessment development, group collaboration, and professional and research activities. Despite these benefits, it is important to carefully consider issues related to academic integrity and privacy, along with the opportunities and challenges presented by this new technology in radiography education.

CONCLUSION

This paper highlights some of the prospects and limitations of the potential applications of ChatGPT in radiography education, underscoring the benefits for both students and educators. However, its implementation must be considered thoughtfully and ethically, taking into account its strengths and limitations.

IMPLICATIONS FOR PRACTICE

Integrating ChatGPT in radiography education has the potential to improve radiography education by improving digital literacy and graduate outcomes of students while streamlining the preparation process for educators. However, ethical implementation is vital for optimal outcomes.

What Are They Thinking? Exploring College Students' Mental Processing and Decision-Making About COVID-19 (Mis)Information on Social Media

More and more, people are abandoning the active pursuit of news, assuming instead that important information will be pushed to them via their social media networks. This approach to news makes people susceptible to the vast amounts of misinformation online, yet research on the effects of this kind of engagement is mixed. More research is needed on technology incidental learning effects, defined as changes in knowledge, attitudes, beliefs, and behaviors as a result of being exposed to information while pursuing goals other than learning (e.g., entertainment). In this study, we examined how 51 college students responded to incidental exposure to accurate and inaccurate COVID-19 information delivered via a simulated social media environment. Participants' verbalizations during think-aloud protocols indicated numerous mental processes including cognition, metacognition, epistemic cognition, motivation, and emotions. Positively valenced mental processing was more often expressed with accurate COVID-19 information and negatively valenced mental processing was more often verbalized with misinformation. Negatively valenced evaluations of knowledge claims and sources predicted less engagement with COVID-19 misinformation posts. However, in many cases the relations among verbalized mental processing and behavioral responses were complex or non-obvious. For example, participants' positive metacognition and epistemic cognition verbalizations decreased their likelihood of engaging with accurate COVID-19 information, whereas positive interest was associated with an increased likelihood of engaging with misinformation. Our findings have implications for how to accurately infer people's beliefs and intentions from their social media behaviors and how to design interventions to help people be more active and thoughtful consumers of online information.

Identifying the effects of scaffolding on learners' temporal deployment of self-regulated learning operations during game-based learning using multimodal data

Introduction

Self-regulated learning (SRL), or learners' ability to monitor and change their own cognitive, affective, metacognitive, and motivational processes, encompasses several operations that should be deployed during learning including Searching, Monitoring, Assembling, Rehearsing, and Translating (SMART). Scaffolds are needed within GBLEs to both increase learning outcomes and promote the accurate and efficient use of SRL SMART operations. This study aims to examine how restricted agency (i.e., control over one's actions) can be used to scaffold learners' SMART operations as they learn about microbiology with Crystal Island, a game-based learning environment.

Methods

Undergraduate students (N = 94) were randomly assigned to one of two conditions: (1) Full Agency, where participants were able to make their own decisions about which actions they could take; and (2) Partial Agency, where participants were required to follow a pre-defined path that dictated the order in which buildings were visited, restricting one's control. As participants played Crystal Island, participants' multimodal data (i.e., log files, eye tracking) were collected to identify instances where participants deployed SMART operations.

Results

Results from this study support restricted agency as a successful scaffold of both learning outcomes and SRL SMART operations, where learners who were scaffolded demonstrated more efficient and accurate use of SMART operations.

Discussion

This study provides implications for future scaffolds to better support SRL SMART operations during learning and discussions for future directions for future studies scaffolding SRL during game-based learning.

Adapting the Motivated Strategies for Learning Questionnaire to the Japanese Problem-Based Learning Context: A Validation Study

The COVID-19 pandemic has greatly changed medical education, and medical trainees' self-regulation has become more emphasized. In Japan, the concept of self-regulated learning has not been fully applied in health profession education due to a lack of effective measurement tools. We aimed to validate the translated Japanese version of the Motivated Strategies for Learning Questionnaire in the context of Problem-Based Learning (J-MSLQ-PBL). The questionnaire employs a seven-point Likert-type scale with 81 items and is categorized into two sections: motivation and learning strategies. An exploratory factor analysis (EFA) was conducted by using Promax rotation to examine the factor structure of the scale, using the collected data from 112 Japanese medical students. Factor extraction was based on a scree plot investigation, and an item was accepted when the factor loading was ≥0.40. In the motivation section, the extracted factors from the EFA were well aligned with the subscales of the original MSLQ, including "Self-Efficacy for Learning and Performance", "Task Value", "Self-Efficacy for Learning and Performance", "Test Anxiety", "Extrinsic Goal Orientation", and "Intrinsic Goal Orientation". In the learning strategies, the extracted factors poorly matched the structure of the original subscales. This discrepancy could be explained by insufficient translation, the limited sample size from a single medical school, or cross-cultural differences in learning strategies between Western and Japanese medical students. Only the motivation part of the J-MSLQ-PBL should be implemented to measure the competency elements of self-regulated learning in Japan.

Effects of regulated learning scaffolding on regulation strategies and academic performance: A meta-analysis

Education research is increasingly focused on fostering self-regulated learning (SRL) and socially shared regulation of learning (SSRL) among students. However, previous meta-analyses have rarely focused on the specific types of regulated learning scaffolding. Therefore, this meta-analysis examines the effects of different types of regulated learning scaffolding on regulation strategies and academic performance. A total of 46 articles met the inclusion criteria and were included in the final analysis. The findings showed that overall, regulated learning scaffolding had a moderate effect (g = 0.587). In addition, moderation analyses were performed using a random effects model that focused on four types of scaffolding. The results showed that overall, composite tools had the greatest effect, while the most useful scaffolding for SRL and SSRL were group awareness tools (g = 0.61) and composite tools (g = 0.53), respectively. In terms of learning outcomes, composite tools had the greatest effect on regulation strategies, while intelligent pedagogical agents had the greatest effect on academic performance. We also performed a meta-regression analysis to identify the moderators that had the greatest influence on the effects of regulated learning scaffolding. The results showed that grade level, academic subject, and cooperation all had a significant impact. In conclusion, these findings provide evidence for validating the effectiveness of four regulated learning scaffolding and for discovering their function for SSRL, and presented some practical implications of our findings.