ETR&D

Generalist primary school computer science (CS) teachers are often reluctant to introduce CS activities that go beyond CS unplugged tasks. To address this challenge, we drew from constructive alignment principles to implement a new programming modality for primary school: the handwriting programming language (HPL). HPL brings programming activities closer to existing teaching practices by enabling students to write instructions on paper, take a picture, and have an agent execute them. HPL’s applicability in classrooms was investigated in two stages. First, 49 primary school teachers evaluated two alternative programming modalities—HPL and an equivalent paper-based Tangible Programming Language—using the technology acceptance model (TAM). As teachers preferred HPL, we then conducted a 3-session quasi-experimental study with 143 public school students (aged 9–10) to compare HPL’s acceptance (with the TAM) and learning outcomes (with a validated test) to the established Scratch programming language. The findings indicate that: (i) over 80% of teachers were willing to use HPL to teach CS in class, irrespective of gender or prior experience; (ii) HPL-students exhibited less trial-and-error behaviour than Scratch-students (fewer attempts, more time between attempts); (iii) students perceived HPL as positively as Scratch; (iv) HPL-students learned as much as Scratch-students. In conclusion, HPL is an accessible, accepted, and pedagogically meaningful means of teaching CS that is as efficient as Scratch to teach CS in primary school. HPL’s efficiency and acceptance by teachers and students suggests that handwriting-based programming languages may help shift primary school CS teaching practices, and make CS education more widespread, bringing us closer to CS for all.

The reading ability of hearing-impaired students is essential for their participation in mainstream society. However, previous studies have shown that they may encounter obstacles due to a lack of interest or limitations in reading communication systems. Augmented reality (AR) has been noted to provide immersive learning environments, collaborative assistance, and in-time resources for improving reading experience and motivation. While previous studies have developed mobile reading environments tailored for hearing-impaired students, the incorporation of pedagogical approaches within immersive AR reading environments remains unexplored. Accordingly, this study investigated the effects of immersive AR environments on hearing-impaired students’ reading with a quasi-experiment. Sixty-five hearing-impaired students’ reading achievement, perceptions, and behaviours were analysed with one-way analysis of covariance and lag sequential analysis. The result indicated that the immersive AR learning environment incorporating the DEEP reading strategy (i.e., Developing self-regulated reading, Experimental exploration, Express and creative construction, and Pluralism) improved hearing-impaired students’ reading achievement, perceptions, and behaviours. Students with the immersive AR reading strategy exhibited more interactive-oriented behaviours and high levels of cognitive attainment (e.g., experiential exploration, creative construction, and problem-solving). This study contributed to existing hearing-impaired teaching practices by revealing what essential behaviour teachers should consider and how to design an immersive AR learning environment.

The generalization of the cognitive theory of multimedia learning to immersive virtual reality (IVR) learning contexts has been increasingly examined; for example, there has been an exploration of redundancy effects on science learning using IVR technology. However, studies on how well multimedia principles such as redundancy work in IVR learning with humanities-related content has been limited. This work therefore aimed to explore the redundancy effects of immersive virtual literary reading on students’ humanities learning by evaluating their empathy, cognitive load, and reading comprehension with consideration of the moderating effects of their learning backgrounds. A between-subjects design with two modes of presentation format (auditory narrative only vs. auditory narrative and on-screen text) involved 70 higher education students who were randomly assigned to two groups, with 35 students in each condition. Results showed that the students’ learning background moderated their perceived empathy but not their cognitive load and reading performance when reading redundant virtual information. Redundancy design of instructional content in IVR learning environments was verified as reducing cognitive load. Moreover, reading an immersive virtual literary novel with redundant information design was likely not detrimental to the students’ higher-level reading comprehension performance, but this was not the case for their lower-level reading comprehension.

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.