Improving Metacognitive Ability and Learning Outcomes with Problem-Based Revised Bloom's Taxonomy Oriented Learning Activities

Parwata, I Gusti Agung Lanang; Jayanta, I Nyoman Laba; Widiana, I Wayan

doi:10.28991/esj-2023-07-02-019

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…However, modifications such as discipline-specific tools have been developed to improve its applicability and inter-rater agreement (Crowe et al, 2008;Zheng et al, 2008). Despite these criticisms, Bloom's taxonomy continues to be a valuable resource in higher education (Ramirez, 2017), recognised for its role in assessing personality, developing curriculum, enhancing cognitive skills and promoting deep thinking (Ho & Chng, 2021;Parwata et al, 2023). It aids in creating challenging learning processes, aligning learning outcomes with evaluation methods, enhancing metacognitive abilities and encouraging deeper learning, thus solidifying its status as an essential educational tool.…”

Section: The Role Of Bloom's Taxonomy In Learning and Assessment Designmentioning

confidence: 99%

Race with the machines: Assessing the capability of generative AI in solving authentic assessments

Nguyen Thanh,

Vo,

Nguyen Nhat

et al. 2023

AJET

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In this study, we introduce a framework designed to help educators assess the effectiveness of popular generative artificial intelligence (AI) tools in solving authentic assessments. We employed Bloom’s taxonomy as a guiding principle to create authentic assessments that evaluate the capabilities of generative AI tools. We applied this framework to assess the abilities of ChatGPT-4, ChatGPT-3.5, Google Bard and Microsoft Bing in solving authentic assessments in economics. We found that generative AI tools perform very well at the lower levels of Bloom's taxonomy while still maintaining a decent level of performance at the higher levels, with “create” being the weakest level of performance. Interestingly, these tools are better able to address numeric-based questions than text-based ones. Moreover, all the generative AI tools exhibit weaknesses in building arguments based on theoretical frameworks, maintaining the coherence of different arguments and providing appropriate references. Our study provides educators with a framework to assess the capabilities of generative AI tools, enabling them to make more informed decisions regarding assessments and learning activities. Our findings demand a strategic reimagining of educational goals and assessments, emphasising higher cognitive skills and calling for a concerted effort to enhance the capabilities of educators in preparing students for a rapidly transforming professional environment. Implications for practice or policy Our proposed framework enables educators to systematically evaluate the capabilities of widely used generative AI tools in assessments and assist them in the assessment design process. Tertiary institutions should re-evaluate and redesign programmes and course learning outcomes. The new focus on learning outcomes should address the higher levels of educational goals of Bloom’s taxonomy, specifically the “create” level.

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Section: The Role Of Bloom's Taxonomy In Learning and Assessment Designmentioning

confidence: 99%

Race with the machines: Assessing the capability of generative AI in solving authentic assessments

Nguyen Thanh,

Vo,

Nguyen Nhat

et al. 2023

AJET

View full text Add to dashboard Cite

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Generative AI’s Impact on Critical Thinking: Revisiting Bloom’s Taxonomy

Gonsalves

2024

Journal of Marketing Education

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The integration of generative artificial intelligence (AI) tools like ChatGPT in education has raised concerns that students may become dependent on AI-generated solutions, potentially stifling the development of critical thinking skills. Compounding this issue is the fact that Bloom’s Taxonomy—the widely used framework for designing educational goals—fails to address the cognitive demands of AI-assisted learning. This exploratory study presents a revised framework that incorporates AI-specific competencies, offering a more relevant model for nurturing critical thinking in an AI-driven environment. Using a conceptual approach supported by empirical evidence from MSc Marketing students’ interactions with AI tools over 4 weeks, the study found that AI can both enhance and challenge critical thinking across cognitive, affective, and metacognitive domains. Key elements such as melioration, ethical reasoning, collaboration, and reflective thinking were identified as critical for developing deeper engagement with AI-generated content. The framework proposes 12 propositions that inform future research and pedagogical strategies. This study outlines a research agenda for examining AI’s impact on cognitive development, serving as a resource for educators, policymakers, and researchers seeking to adapt teaching methods for AI-assisted education.

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Pemanfaatan Media Video pada Model Pembelajaran Problem Based Learning

Ardiansyah,

Meyko Panigoro,

Nurul Maulida Alwi

2024

j. penelit. dan pengemb. pendidik.

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Kemampuan berpikir yang rendah dari siswa dalam menganalisa isu permasalahan serta kurangnya pemanfaatan media pembelajaran dalam proses pembelajaran menggunakan model pembelajaran berbasis masalah sehingga menyebabkan capaian pembelajaran kurang maksimal. Tujuan penelitian ini untuk menganalisis penerapan media video dalam model pembelajaran PBL terhadap pemecahan masalah. Pre-experimental design dengan menggunakan pretest-posttest design merupakan pendekatan yang digunakan dalam penelitian ini. Populasi dan sekaligus sampel penelitian ini adalah siswa kelas VII yang berjumlah 30 orang. Teknik pengumpulan data dalam penelitian ini menggunakan observasi langsung, dokumentasi dan alat instrumen tes. Analisis data menggunakan SPSS 26 untuk menganalisis skor mean sebelum dan sesudah pengujian, hasil uji normalitas, homogenitas serta hasil uji T sampel tunggal. Hasil uji-T one sampel, penggunaan video pembelajaran dalam model pembelajaran berbasis masalah kelas pra eksperimen berdampak pada kemampuan siswa dalam memecahkan masalah. Nilai signifikansi yang kurang dari 0,05 menunjukkan penggunaan video berdampak pada kemampuan siswa dalam memecahkan masalah. Implikasi penelitian ini bahwa penggunaan media video dalam pendekatan pembelajaran PBL dapat membantu dalam pemecahan masalah.

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Improving Metacognitive Ability and Learning Outcomes with Problem-Based Revised Bloom's Taxonomy Oriented Learning Activities

Cited by 3 publications

References 27 publications

Race with the machines: Assessing the capability of generative AI in solving authentic assessments

Race with the machines: Assessing the capability of generative AI in solving authentic assessments

Generative AI’s Impact on Critical Thinking: Revisiting Bloom’s Taxonomy

Pemanfaatan Media Video pada Model Pembelajaran Problem Based Learning

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