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All Journal Jurnal Ekonomi, Teknologi dan Bisnis Insight : International Journal of social research
Elok Nur Affah Al Akromi
Universitas Islam Negeri Siber Syekh Nurjati, Indonesia
Humanities Astronomy Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering

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Training the Trainer: Measuring the Long-Term Effectiveness of AI Upskilling Programs for Indonesian Educators Elok Nur Affah Al Akromi
Jurnal Ekonomi, Teknologi dan Bisnis Vol. 4 No. 12 (2025): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/5975rm80

Abstract

Indonesia's national artificial intelligence (AI) education roadmap (2025–2045) positions teacher AI competency as foundational to its Golden Generation vision, yet the long-term effectiveness of AI upskilling programs for Indonesian educators remains empirically unexamined. This study aims to evaluate the extent to which AI-related competencies are retained over time, identify key factors influencing sustained AI integration among teachers, and compare the effectiveness of different upskilling programs across regional contexts. This longitudinal mixed-methods study measured the durability of AI competency gains among 347 in-service K–12 teachers across urban, peri-urban, and remote regional strata over four measurement waves: pre-intervention, immediate post-intervention, six-month follow-up, and twelve-month follow-up. Participants were drawn from two nationally deployed AI upskilling programs  Platform Merdeka Mengajar (PMM) and Microsoft Elevate   and assessed using a validated four-subscale questionnaire, semi-structured interviews, and structured classroom observation checklists. Results revealed a consistent "spike-and-decay" trajectory across all groups, with teachers retaining an average of only 63.5% of post-intervention competency gains at the twelve-month wave. Microsoft Elevate participants demonstrated significantly superior retention compared to PMM participants, and remote-stratum teachers experienced the steepest decay. Post-intervention AI self-efficacy, peer collaboration frequency, and perceived program relevance emerged as the strongest predictors of sustained behavioral integration. Qualitative findings identified infrastructure deficits, institutional isolation, curricular misalignment, and confidence erosion as primary disinvestment mechanisms. The study concludes that sustainable AI teacher competency requires a systems-level response encompassing mandatory post-training support, differentiated regional resourcing, and curriculum-embedded AI learning communities.
Climate Change and Eco-Anxiety in Contemporary Climate Fiction (Cli-Fi) Elok Nur Affah Al Akromi; Jan Mohammad Miakhil
International Journal of Social Research Vol. 3 No. 5 (2025): Insight : International Journal of Social Research
Publisher : Worldwide Research Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/insight.v3i5.103

Abstract

Climate change has precipitated not only an ecological crisis but a profound psychological one, giving rise to eco-anxiety a chronic, multidimensional emotional response to environmental degradation that is increasingly prevalent across global populations. Despite the parallel growth of climate fiction (cli-fi) as a culturally significant literary genre, scholarship has yet to systematically examine how contemporary cli-fi represents eco-anxiety as both thematic content and formal principle. This study addresses that gap through a qualitative ecocritical and affective literary analysis of six internationally significant cli-fi novels: Kingsolver's Flight Behavior (2012), Powers' The Overstory (2018), El Akkad's American War (2017), Jemisin's The Fifth Season (2015), Offill's Weather (2020), and Ghosh's Gun Island (2019). Employing thematic analysis supported by NVivo (Version 14) and guided by an ecocritical coding rubric derived from the eco-anxiety frameworks of Albrecht (2019), Clayton and Karazsia (2020), and Pihkala (2022), the study analyzed 312 coded passages across six eco-anxiety themes. Findings reveal that ecological grief (29.8%) and anticipatory loss (25.6%) constitute the dominant affective registers of the corpus, followed by helplessness and powerlessness (22.1%), solastalgia (21.2%), affective resilience (18.3%), and intergenerational despair (16.7%). The study further demonstrates that eco-anxiety is not merely depicted thematically but formally enacted through narrative fragmentation, temporal disruption, and second-person address. Cross-cultural analysis reveals that postcolonial cli-fi encodes eco-anxiety as inseparable from racial and political dispossession, challenging Western-centric psychological frameworks. The study proposes an original "eco-anxiety poetics" framework with significant implications for ecocritical scholarship, environmental education, climate communication, and therapeutic bibliotherapy practice.
Co-Authors Jan Mohammad Miakhil