By Dr Cherie Lucas (UNSW School of Population Health), Associate Professor Anita Heywood (UNSW Associate Dean Education (Quality)), Dr Husna Razee (UNSW School of Population Health) and Dr Ben Harris-Roxas (UNSW School of Population Health)
Dr Cherie Lucas is a #UNSWNexus Fellows – learn more about the program here.
Published 25 September 2024
Higher-education teachers face unprecedented challenges in assessing how students arrive at answers, given the accessibility of generative AI. These tools can often produce reasonable responses, blurring the distinction between genuine understanding and algorithmic output. Reflective practice can play a pivotal role in encouraging authentic learning and providing additional artefacts for educators to assess learning. Reflection on one’s practice or learning focusses on the process of learning, revealing new insights and understandings that are relevant to developing critical thinking and problem-solving skills, improving learning and developing lifelong learning skills.
Assessment drives student learning, and sometimes students do not engage in meaningful metacognition through reflection in favour of arriving at an assessable outcome.
Reflective practice, although not a novel concept, holds renewed significance in contemporary education, particularly as professional bodies increasingly expect graduates to develop reflective-practitioner skills.
Western practices of reflecting about “how we think” originated in the early 20th century, driven by seminal philosopher John Dewey, and have evolved into pedagogical strategies aimed at fostering deeper learning and intellectual growth. At its core, reflective practice encourages individuals to introspectively examine their thought processes, actions, values, biases and approaches to learning to make better-informed decisions. This enhances their ability to navigate the complexities and uncertainties inherent in academic and professional domains.
The essence of reflective practice lies in its emphasis on understanding the journey, rather than fixating solely on the destination.
By dedicating time and attention to articulating and unravelling thought processes, learners can uncover invaluable insights into their problem-solving approaches, analytical reasoning and decision-making strategies.
This nuanced approach not only highlights areas of strength and improvement but also nurtures a more profound engagement with and application of subject matter to real-life contexts.
Further, in an era of increasingly sophisticated large language models, reflective practice takes on heightened relevance. Generative AI can yield responses that mimic human comprehension but may also harbor biases or inaccuracies — referred to as flaws, “hallucinations" or plausible fabricated “confabulations”. Engaging students in critical reflection on these outputs encourages them to scrutinise the underlying assumptions, biases and limitations of AI technologies. This process not only sharpens their judgement but also cultivates a healthy scepticism and curiosity, essential for using generative AI responsibly.
Generative AI has been used to produce effective writing, including reflections; depending on the types of prompts used, these can be of a high standard.
Reconceptualising the task so that students reflect on the processes (rather than focusing on the final output) may make the tasks less vulnerable to AI.
For instance, educators may incorporate structured reflection exercises where students analyse their decision-making during problem-solving tasks. For example, in an Engineering course, educators may ask students to reflect on their team dynamics and its impact on their design activity. By prompting students to articulate the reasoning behind their choices, educators can gain deeper insights into the students’ cognitive processes and can provide targeted feedback to enhance learning outcomes. Alternatively, tasking students to write reflections as a formative task to support summative learning may enhance learning.
Furthermore, integrating reflective practice into curriculum design can scaffold students' development of metacognitive skills – the ability to monitor and regulate one's own thinking. This metacognitive awareness is crucial for lifelong learning and empowers students to adapt to evolving challenges in their academic and professional journeys.
While generative AI technologies offer unprecedented opportunities for enhancing educational experiences, the importance of reflective practice in nurturing critical thinking and problem-solving skills is more important now than before generative AI’s emergence. By prioritising the understanding of students' cognitive processes over mere outcomes, educators can foster a learning environment that values inquiry, creativity and intellectual rigor. Reflective practice not only equips students to navigate the complexities of generative AI but also cultivates a mindset of continuous growth and inquiry – one that is essential for a lifelong learning process.
Is reflective practice the answer to enhancing critical thinking skills in the era of generative AI?
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References
- Fischer J, Bearman M, Boud D, Tai J. How does assessment drive learning? A focus on students' development of evaluative judgement. Assessment and Evaluation in Higher Education. 2024; 49(2):233-245.
- Dewey J. How we think. D.C. Heath & Co; 1910.
- Gibbs G. Learning by doing: a guide to teaching and learning methods. Oxford: Further Education Unit, Oxford Polytechnic; 1988.
- Mortlock R, Lucas C. Generative artificial intelligence (Gen-AI) in pharmacy education: Utilization and implications for academic integrity: A scoping review. Exploratory Research in Clinical and Social Pharmacy. 2024:100481.
- Buckingham Shum S. Generative AI for critical analysis: Practical tools, cognitive offloading and human agency. First International Workshop on Generative AI for Learning Analytics (GENAI-LA): 14th International Learning Analytics and Knowledge Conference (LAK'24), March 18-22, 2024, Kyoto, Japan; 2024.
- Hatem R, Simmons B, Thornton JE. A call to address AI “hallucinations” and how healthcare professionals can mitigate their risks. Curēus (Palo Alto, CA). 2023;15(9):e44720-e44720.
- Brender TD. Chatbot confabulations are not hallucinations – reply. JAMA Intern Med 2023;183(10):1177-1178.
- Li Y, Sha L, Yan L, Lin J, Raković M, Galbraith K, Lyons K, Gašević D, Chen G. Can large language models write reflectively. Computers and education. Artificial intelligence. 2023;4:100140.
- Steuber TD, Janzen KM, Walton AM, Nisly SA. Assessment of learner metacognition in a professional pharmacy elective course. Am J Pharm Educ. 2017;81(10):20-28.
- Tsingos C, Bosnic-Anticevich S, Smith L. Learning styles and approaches: Can reflective strategies encourage deep learning? Currents in pharmacy teaching and learning. 2015;7(4):492-504.