Empowering Social Sciences Educators on the Use of Artificial Intelligence in the Classroom

Key take-aways

Issues to consider

  •  Accuracy Concerns: AI tools may occasionally generate incorrect information or explanations, particularly with specialized political science terminology or emerging theoretical frameworks. Without careful review, these inaccuracies could misinform students.
  •  Over-Reliance on Technology: students might become dependent on immediate feedback, potentially diminishing their capacity for independent critical thinking or self-assessment without technological intervention.
  • Quality of Questions: despite advances in AI, the system may sometimes produce superficial questions that fail to promote deeper analysis or engage with complex political concepts meaningfully. Or the programme analyses the inserted sources superficially, leaving out some of them.
  • Limited Personalization: automated feedback, while consistent, might not address individual students’ specific misconceptions or learning approaches as effectively as personalised human feedback.

Recommendations

  •  Maintain Human Oversight: always review AI-generated questions and feedback before deployment. Set aside dedicated time to verify the accuracy, particularly to be sure that all intended sources are incorporated and meaningful conclusions are drawn from them.
  • Balance Automated and Manual Assessment: use AI tools for formative assessments and basic knowledge checking, while reserving human evaluation for complex analytical tasks and summative assessments. Nevertheless, the AI facilitates the formation of questions for the final exam.
  • Iterative Improvement: document successful and problematic AI prompts to refine your approach over time. Share effective practices with colleagues.
  • Develop Technical Competence: invest time in understanding how to craft effective prompts for AI tools. Small adjustments in instruction phrasing can significantly improve output quality.
  • Evaluate Pedagogical Impact: regularly assess whether AI implementation is genuinely enhancing learning outcomes rather than simply increasing efficiency. Adjust your approach based on these evaluations. Collecting feedback from students how useful these tests are, is a good starting point.
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