Algorithmic learning or learner autonomy? Rethinking AI’s role in digital education DOI
Dech-siri Nopas

Qualitative Research Journal, Год журнала: 2025, Номер unknown

Опубликована: Апрель 14, 2025

Purpose The purpose of this study is to critically investigate the effects artificial intelligence (AI)-driven learning environments on learner autonomy, knowledge co-construction and digital equity in Thailand’s online education context. It aims analyze how algorithmic tools AI-based systems shape learners' educational experiences, particularly focusing whether these technologies enhance or constrain autonomy collaborative interactions. Additionally, it evaluates ethical social implications, divide, biases transparency AI-mediated processes. seeks provide actionable insights recommendations for policymakers, educators developers optimize AI integration inclusive lifelong learning. Design/methodology/approach This research adopts a qualitative case methodology involving in-depth, semi-structured interviews, participant observations detailed document analysis from 30 diverse participants, including urban rural learners, instructional designers. Employing actor-network theory (ANT) posthumanist theoretical frameworks, examines interactions between human non-human actors within AI-driven environments. approach allows comprehensive exploration participants' lived perceptions with technologies. Triangulation multiple data sources ensures depth reliability, providing nuanced into influence processes equity. Findings identifies platforms as having dual impacts simultaneously enabling greater self-directed through personalized guidance real-time feedback while imposing constraints that restrict intellectual exploration. AI-facilitated effectively organizes structures peer yet often results depersonalized, transactional communication lacking deep engagement. Furthermore, significant inequities are evident, learners disproportionately disadvantaged due limited technological infrastructure embedded platforms. These highlight critical need inclusive, transparent design practices ensure equitable access meaningful agency. Research limitations/implications qualitative, context-specific nature limits generalizability findings beyond environment. rapidly evolving suggests reflect specific temporal context, necessitating continuous updates. Participant selection bias may have influenced findings, participants potentially holding strong pre-existing opinions education. Future studies should consider longitudinal analyses understand long-term impacts, comparative cross-cultural validate deeper biases, fairness considerations tools, they affect socio-economic groups. Practical implications Practically, underscores necessity designing genuinely empower thinking rather than overly dictate pathways. Educational practitioners technology implement decision-making processes, evaluate recommendations. Policies must prioritize expansion literacy programs reduce urban-rural disparities. pedagogical integrate human-centric approaches complement ensuring serve enhance, replace, essential Social emphasizes holds potential democratizing by offering adaptive experiences. However, also warns risks associated reinforcing existing inequalities, learners. Addressing divides targeted policy interventions, infrastructural investments fostering inclusivity By accessible beneficial all demographics, societies can leverage tool broad-based empowerment development mechanism perpetuating exclusion. Originality/value contributes original Thai context – areas relatively underexplored literature. uniquely integrating perspectives, offers sophisticated understanding interplay humans settings. empirical deliver crucial evidence-based educators, policymakers aiming ethically inclusively Ultimately, enriches ongoing discussions balancing advancement human-centric, socially responsible practices.

Язык: Английский

Algorithmic learning or learner autonomy? Rethinking AI’s role in digital education DOI
Dech-siri Nopas

Qualitative Research Journal, Год журнала: 2025, Номер unknown

Опубликована: Апрель 14, 2025

Purpose The purpose of this study is to critically investigate the effects artificial intelligence (AI)-driven learning environments on learner autonomy, knowledge co-construction and digital equity in Thailand’s online education context. It aims analyze how algorithmic tools AI-based systems shape learners' educational experiences, particularly focusing whether these technologies enhance or constrain autonomy collaborative interactions. Additionally, it evaluates ethical social implications, divide, biases transparency AI-mediated processes. seeks provide actionable insights recommendations for policymakers, educators developers optimize AI integration inclusive lifelong learning. Design/methodology/approach This research adopts a qualitative case methodology involving in-depth, semi-structured interviews, participant observations detailed document analysis from 30 diverse participants, including urban rural learners, instructional designers. Employing actor-network theory (ANT) posthumanist theoretical frameworks, examines interactions between human non-human actors within AI-driven environments. approach allows comprehensive exploration participants' lived perceptions with technologies. Triangulation multiple data sources ensures depth reliability, providing nuanced into influence processes equity. Findings identifies platforms as having dual impacts simultaneously enabling greater self-directed through personalized guidance real-time feedback while imposing constraints that restrict intellectual exploration. AI-facilitated effectively organizes structures peer yet often results depersonalized, transactional communication lacking deep engagement. Furthermore, significant inequities are evident, learners disproportionately disadvantaged due limited technological infrastructure embedded platforms. These highlight critical need inclusive, transparent design practices ensure equitable access meaningful agency. Research limitations/implications qualitative, context-specific nature limits generalizability findings beyond environment. rapidly evolving suggests reflect specific temporal context, necessitating continuous updates. Participant selection bias may have influenced findings, participants potentially holding strong pre-existing opinions education. Future studies should consider longitudinal analyses understand long-term impacts, comparative cross-cultural validate deeper biases, fairness considerations tools, they affect socio-economic groups. Practical implications Practically, underscores necessity designing genuinely empower thinking rather than overly dictate pathways. Educational practitioners technology implement decision-making processes, evaluate recommendations. Policies must prioritize expansion literacy programs reduce urban-rural disparities. pedagogical integrate human-centric approaches complement ensuring serve enhance, replace, essential Social emphasizes holds potential democratizing by offering adaptive experiences. However, also warns risks associated reinforcing existing inequalities, learners. Addressing divides targeted policy interventions, infrastructural investments fostering inclusivity By accessible beneficial all demographics, societies can leverage tool broad-based empowerment development mechanism perpetuating exclusion. Originality/value contributes original Thai context – areas relatively underexplored literature. uniquely integrating perspectives, offers sophisticated understanding interplay humans settings. empirical deliver crucial evidence-based educators, policymakers aiming ethically inclusively Ultimately, enriches ongoing discussions balancing advancement human-centric, socially responsible practices.

Язык: Английский

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