Value‐sensitive design in the praxis of instructional design: A view of designers in situ

British Journal of Educational Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

Abstract Philosophical stances and design frameworks, such as value‐sensitive design, manifest in praxis through enacting specific approaches employing a variety of methods by the designers. Although it could overlap with other frameworks Instructional Design Technology (IDT) field, remains largely unexplored topic instructional for several reasons. As focuses on different stakeholders their values, recognizing contested issue universal we report this paper our empirical work that sought to describe values designers hold/express relation online courses. In study, communicated while discussing philosophies how they manifested designing human‐computer interactions promote authentic learning. Through theoretical lens provide detailed account designers' well showcase artefacts. investigation contribute ongoing discussion generate implications research education. These evolution field. Practitioner notes What is already known about (VSD), methods. VSD overlaps field manifests terms/frameworks. design. Designers' philosophies, judgements play significant role practice, are driving force behind enactment philosophical VSD. The IDT has not sufficiently addressed designer carrying out work. adds Detailed accounts care toward learners support learning environments. Specific examples designed artefacts qualify be designs. A contribution level expertise overall capacity evoke strong judgements. focusing themselves. Implications practice and/or policy scholars need focus more professional characters ethical orientations—as true guarantors design—and less prescriptive models. educators curricula developing so can aware examine them, cultivate and, most importantly, develop successful To able subscribe, enact even criticize expand designerly VSD, students mindset early journey. Designers have own nurture them new help become

Language: Английский

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Examining Teaching Competencies and Challenges While Integrating Artificial Intelligence in Higher Education

TechTrends, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Language: Английский

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How Can (A)I Research This? An Autoethnographic Exploration of Generative AI in Research, Teaching and Instructional Design

Journal of Teacher Education, Journal Year: 2025, Volume and Issue: unknown

Published: March 29, 2025

The autoethnographic study investigates the transformative impact of generative AI on educational research, instructional design, and teaching practices over a 5-month period (May–October 2024). By integrating tools into every phase research process, examines AI’s role as both partner subject inquiry. Field notes, queries, AI-generated outputs were systematically collected, creating corpus for analysis. Grounded in activity theory, this offers reflective narrative evolving work routines designers educators, emphasizing orchestration technology rather than prescriptive best practices. contributes to by documenting use at specific point time, providing foundation future inquiry practical implications education.

Language: Английский

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Analysing nontraditional students' ChatGPT interaction, engagement, self‐efficacy and performance: A mixed‐methods approach

British Journal of Educational Technology, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Generative artificial intelligence brings opportunities and unique challenges to nontraditional higher education students, stemming, in part, from the experience of digital divide. Providing access practice is critical bridge this divide equip students with needed competencies. This mixed‐methods study investigated how interact ChatGPT multiple courses examined relationships between interactions, engagement, self‐efficacy performance. Data were collected 73 undergraduate graduate through chat logs, course reflections artefacts, surveys interviews. interactions analysed using four metrics: prompt number, depth knowledge (DoK), relevance originality. Results showed that numbers ( β = 0.256, p < 0.03) engagement 0.267, 0.05) significantly predicted performance, while did not. Students' DoK r 0.40, 0.01) 0.42, positively correlated Text mining analysis identified distinct interaction patterns, ‘strategic inquirers’ demonstrating performance than ‘exploratory more sophisticated follow‐up questioning. Qualitative findings revealed most first‐time users who initially resistance, they developed growing acceptance. Still, tended use sparingly and, even then, as only a starting point for assignments. The highlights need targeted guidance engineering AI literacy training help leverage effectively higher‐order thinking tasks. Practitioner notes What already known about topic Nontraditional face education, such limited technological access. emergence generative tools presents both addressing educational disparities. Existing studies on implementation predominantly focus traditional students. paper adds Empirical evidence metrics (prompt DoK, originality). Distinct patterns their relationship outcomes. among Implications and/or policy Need explicit instruction skill thinking. Importance providing technology self‐paced learning resources Value developing comprehensive addresses tool capabilities limitations.

Language: Английский

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Developing postgraduate students’ competencies in generative artificial intelligence for ethical integration into academic practices: a participatory action research

Interactive Learning Environments, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: April 7, 2025

Language: Английский

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Perception and Attitudes towards AI (ChatGPT) in Education: A Focus on TESL Students in Perak

Published: Dec. 31, 2024

In this study, we examine how TESL (Teaching English as a Second Language) students think and feel about an AI-based educational tool called ChatGPT. Based on the extant literature drawing from Technology Acceptance Model (TAM) Unified Theory of Use (UTAUT), study utilized systematic review to integrate research studies within both global local contexts with respect AI in education. The results highlight elements including perceived usefulness, Ease use, facilitating conditions, Social influences cultural context that affect students' acceptance AI. offers suggestions for educators legislators, shedding light possible advantages difficulties incorporating into curricula.

Language: Английский

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