ETR&D

AI literacy is becoming increasingly popular in education, yet there has been limited focus on reviewing empirical research on AI literacy assessment. The purpose of this study was to synthesize existing empirical studies on AI literacy assessment, with the aim to understand how AI literacy has been assessed and to inform future AI literacy assessment development. This scoping review evaluates and synthesizes 36 studies on AI literacy assessment published between 2019 and 2024, involving assessment tools, forms of assessment, and reliability and validity evidence related to AI literacy assessment. The review proposes four aspects (i.e., knowledge of AI, AI ethics, affect towards AI, and use of AI) for assessing AI literacy. The results showed that (1) most research focused on assessing primary and secondary school students’ AI literacy; (2) most studies used questionnaires, followed by surveys; (3) most studies used computer-based tests, followed by paper-based tests; (4) most studies assessed participants’ AI knowledge, followed by AI ethics; and (5) only a few studies reported evidence of the reliability and effectiveness of their assessments. Based on the reviewed literature, this study develops an AI literacy framework for people of all ages and from all countries. The findings and directions for future research are also discussed.

There is a growing global interest in the inclusion of coding as early as preschool. However, most coding languages involve reading and writing, leaving non-writing children deprived of the opportunity to develop any kind of coding proficiency. Moreover, many preschool teachers lack the knowledge and self-efficacy necessary for teaching coding. This case study examines the subjective experiences of preschool teachers with no early coding knowledge in implementing the ScratchJr-based Coding as Another Language (CAL) curriculum. Following a four-hour professional development session, two preschool teachers taught coding to 26 children (M = 5.72, SD = 0.33) using the CAL curriculum over seven months. Thematic analysis of semi-structured interviews with teachers identified eight key themes, including initial CS-resistance to coding, pedagogical and cultural curriculum adjustments, overcoming resistance, learning with and from children, enhanced teacherstudent relationship, inter-syllabi learning opportunities, coding-driven community partnership, and potential for self-expression. Quantitative results showed significant improvement in children’s coding knowledge, positioning most at the Fluency stage of CAL proficiency. Results highlighted the effectiveness of the CAL curriculum in building teachers’ coding self-efficacy, despite its relatively brief duration. They further emphasize the importance of curriculum adaptability to diverse educational contexts. These findings support overcoming technology integration barriers in early childhood education. Additionally, the study suggests using coding as a tool for creative self-expression, highlighting its potential beyond technical skill-building. This direction may be further explored to promote emotional and personal growth in both teachers and children, contributing to individual well-being improvement while supporting the integration of STEM-related subject learning in formal curricula.

Digital distraction in education describes the interruption of learner’s concentration during academic tasks. With the increase in digital learning, there is a need for a review to synthesize research on digital distraction. This systematic review examined 26 articles using the DISCAR process (design, inclusion/exclusion, searching and screening, coding, analyzing/synthesizing, reporting) and was guided by the Technology-Personal-Environment (TPE) framework. The review examined causes and consequences, and strategies to prevent/reduce digital distraction. Measures used, modalities studied, and devices used in digital distraction research were also synthesized. Causes for digital distraction were technology distractors (51.95%), personal needs (37.66%), and instructional environment (10.39%) factors. Consequences for digital distraction included personal performance issues (66.67%), ineffective classroom instruction (23.33%), and problematic technology use (10%). Prevention strategies included classroom environment regulations (41.03%), technology controls (30.77%), and personal behavioral interventions (28.21%). The findings have implications for instructors, students, administrators, instructional designers and researchers. This systematic review adopted a multi-faceted approach to effectively mitigate digital distractions.

Good teaching requires a professional vision of the relevant dimensions of teaching quality and their interrelationships. For example, classroom management is necessary but insufficient for providing effective instructional support. Thus, teacher education should foster a multiperspective professional vision of these dimensions of teaching quality as a basis for implementing appropriate teaching actions. Research shows that professional vision can be promoted when preservice teachers analyze classroom videos. However, acquiring a multiperspective professional vision is more complex than a single perspective. Furthermore, preservice teachers have different entry levels and developmental trajectories. Individual learning requirements and the more complicated task demands can potentially be met through virtual learning environments and additional support tools implemented during video analysis. We used a video-based assessment with an open response format and investigated (1) the effect of a video-based virtual learning environment on promoting multiperspective professional vision in elementary science education and (2) the effect of additional support tools (modeling videos and prompts) implemented during video analysis. A quasi-experimental pre-post-follow-up study with 145 preservice teachers showed that a basic virtual learning environment improved participants’ multiperspective professional vision compared to an untreated control group in the short and long term. The additional support tools in the enriched virtual learning environment did increase preservice teachers’ performance even more while training professional vision but not in the post- and follow-up tests. Therefore, teacher education programs should consider the benefits of video-based virtual learning environments for an individualized promotion of professional vision. Further research on effective digital support tools is needed.

Hybrid Flexible (HyFlex) instruction offers a promising approach to enhancing flexibility and student engagement in undergraduate education. Yet, challenges related to technology, faculty readiness, and equity remain. This systematic review serves to explore current trends in the peer-reviewed literature on HyFlex learning between 2013 and 2023, specifically within the context of undergraduate education. The PRISMA principles were used as a guide to complete this review. Researchers conducted a broad search of HyFlex instruction research using five electronic databases. A total of 1,512 articles were screened as part of the systematic review. A total of 46 articles met the inclusion criteria. The results of the systematic review revealed that between 2013 and 2021 there were very few publications per year related to HyFlex instruction in undergraduate education. However, the number of publications increased significantly in 2022 and 2023. The results of the systematic review also revealed that research in HyFlex instruction in undergraduate education is a global and highly collaborative endeavor. In terms of major research trends, the systematic review also served to better understand the context in which the implementation of HyFlex instruction in undergraduate education was explored including the subject–matter of the instruction, number of participants, and research methodology. Of the 46 studies reviewed, the majority reported neutral findings, indicating that HyFlex instruction had neither a distinctly positive nor negative impact. Key findings from the research focused on HyFlex instruction design and learning strategies in undergraduate education are also discussed.

The research focus on teacher questions is justified by previous research emphasizing the essential role of questions in facilitating meaningful learning in science. Analysis of teacher questions has traditionally been based mainly on manual coding, which is extremely labour intensive. In this study we explore how both machine learning and large language models can be used for this purpose. Whereas machine learning approaches involve supervised training with extensive data, pre-trained large language models operate through prompt engineering. ​​The​ automatic speech recognition text outputs of 23 physics lessons on the same topic from 23 science teachers were analysed with variety of techniques. The results revealed that the large language model approaches improved with few-shot approaches compared to zero-shot ones. Furthermore, few shot approaches outperformed the supervised machine learning approaches, yet human- and hand-crafted approaches continue to demonstrate their relevance. ​​Implications for​ science teaching and learning are discussed.

Native language (L1) reading studies have established that text type, or genre, strongly influences reading comprehension, and narrative, or story-based, texts are easier to recall and understand than expository, or informational, texts, indicating that the comprehensibility of the content may differ depending on the genre in which it is presented. However, the effects of text genres on reading comprehension have rarely been the focus of target language (L2) reading mainly due to methodological difficulty because because L2 reading is a highly complex process that involves additional cognitive demands beyond those of L1 reading. For this problem, this investigation proposes a recent “knowledge structure (KS)” network analysis approach to visually describe and distinguish the reading processes and outcomes that may be triggered by the use of text genre in L2 reading. University mixed proficiency Korean English language learners (n = 616) were randomly assigned to one of 8 conditions that all involved a pre-reading task in L1 or L2 (as a sorting task), reading a text (either narrative or expository), then from memory a post-reading task in L1 or L2 (as a summary writing), and finally a comprehension posttest. All of the participants’ sorting and essay artifacts were converted into Pathfinder Networks, a graph-theoretic psychometric networks scaling measure, that were visually and statistically compared with each lesson text’s Pathfinder Networks they read. The findings have practical implications for L2 reading instruction. Narrative texts would be more beneficial to L2 readers who do have lower L2 proficiency because of its greater easy of processing, while expository texts would be more beneficial to L2 readers who have enough prior knowledge of to-be-learned content because of its tendency to integrate content with prior knowledge.

This paper describes the design principles and impact of an online asynchronous short course “Key Ideas in Mentoring Mathematics Teachers”, contributing to the professional development (PD) of prospective and practicing school-based mentors of mathematics teachers. The course was designed to empower mentors with knowledge about research informed practice and instil in them a welcoming stance towards mathematics education research. An Architecture of Online Engagement and a Vignette Activity Sequence approaches were employed in the design of the course, as means of supporting the participants to critically reflect on their teaching practices through engagement with topic-specific mathematics education research and on the implications for their mentoring practices. With a focus on the Vignette Activity Sequence (VAS) in particular, we discuss the potential impact and value of this approach to designing an online asynchronous professional development course in general, but also in the context of mentors of mathematics teachers. This paper’s contribution lies in the discussion of design principles of a PD course that successfully engage mentors with mathematics education research literature, while allowing them to reflect on their own practices and experiences.

This article presents the results of a multiple case study that explored the ways learning, design, and technology (LDT) scholars negotiate issues of social justice in their practice and research. Using Stake’s (2009) multiple case study, we examined the design practices of 4 scholars, looking across contexts to understand participants’ design practices, as well as the connections between those practices, their perspectives, and the local context. We found that attending to social justice requires a reflexive, reflective approach situated within understandings related to designer positionality and power. Design practices were employed to address justice-based tensions that emerged around project goals, perceived roles, and power dynamics. This study provides insight into the ways current scholars are taking up issues of social justice by engaging in a critical, responsive approach to design.