Assessment Analysis: Concepts, Types, and Modern Approaches

Risks:

• Possibilities of cheating and misuse of generative artificial intelligence (especially in summative assessments).
• Lack of direct interaction may make it more difficult to interpret students’ responses and understand their learning processes.
• Technical difficulties and the digital divide among students may affect the fairness and reliability of assessment.

Adaptations and Recommendations:

• Use a combination of different assessment methods and tools (e.g., quiz + forum + project + automated formative assessment) to reduce the risk of cheating and increase the authenticity of evaluation.
• Clearly communicate criteria, purpose, and expectations related to assessment, and involve students in understanding the criteria (transparent assessment) to support the development of self-regulation and the effective use of feedback. (Nicol–Macfarlane–Dick, 2006; Carless–Boud, 2018).
• Provide automated yet personalized feedback, for example, through tools with built-in learning analytics and AI support.

• Integrate formative assessment into the learning process, encouraging student reflection and self-regulation rather than relying solely on summative assessments. (Divjak–Svetec–Horvat, 2024).