Automated Assessment in Higher Education

3. Examples of Technologies and Approaches

• Automated quizzes – most commonly include multiple-choice questions, true/false items, matching tasks, and numerical answers. This type of assessment provides immediate feedback and can be widely used in both formative and summative assessment, especially in large groups (Divjak et al., 2022; Clark, 2012).
• Essay analysis tools – software such as GrammarlyGO and tools based on large language models (LLMs), such as ChatGPT, are increasingly used for automatic analysis of grammar, coherence, argumentation, and style. These tools support self-assessment and provide personalised feedback to students (Kumar et al., 2024).
• Automated portfolio assessment – modern systems integrated into LMS environments use rubrics and checklists for structured evaluation of student work. This automates the allocation of points based on predefined criteria (e.g., evidence of reflection, quality of argumentation, clarity of presentation) (Khasawneh et al., 2025). For example, in the Mahara system or the Moodle Assignment activity, a student submits multiple artefacts (an essay, an infographic, a video), and the instructor selects a rubric that automatically assigns points depending on achievement levels. The system then generates a summary of scores and a graphical representation of each student's progress.
• AI and LLM-based systems – a new generation of tools based on artificial intelligence, including LLMs such as ChatGPT, enables personalised feedback, supports self-reflection, and fosters metacognitive development. Recent research shows that LLMs are effective in assessing student work (Floden, 2024), as well as in assisting with problem-solving and project-oriented tasks (Divjak et al., 2025).