Analysis of educational technology according to established criteria

In groups, analyze six unique aspects of AI applications in higher education using previously established criteria for evaluating educational technology (pedagogical value, alignment with learning outcomes, interactivity and engagement, accessibility and inclusiveness, ease of use, integration into the teaching process, monitoring and evaluation, reliability and stability, sustainability and costs, development of attitudes and values):

• Personalized learning: AI systems can adapt content and tasks to the pace and prior knowledge of students, recommend additional resources, and offer individual learning paths.
• Automated assessment and feedback: AI can grade short answers, essays, or programming code and provide rapid feedback to students, saving teachers time for more complex forms of evaluation.
• Learning analytics and predictive models: AI-based systems can analyze patterns in student behavior (e.g., frequency of sign-ups, time spent on assignments) and predict the risk of failure, allowing teachers to intervene in a timely manner.
• Intelligent virtual assistants: Chatbots and voice assistants can provide 24/7 support to students by answering questions about courses, deadlines, and procedures, and by offering explanations of course content.
• Courseware generation: AI tools can create quizzes, simulations, article summaries, or data visualizations, enriching the teaching process and encouraging diversity in learning.
• Research support: AI can help search and analyze scientific literature, discover patterns in large data sets, and generate research hypotheses, reducing the time required for scientific work.

Instructions:

• Each group selects one of the listed aspects of AI application by having a group representative report to the instructor.
• Analyze the selected aspect according to all the criteria from the rubrics in the criteria form (the criteria form is found in the previous activity Preparation). Assign grades (5 = excellent, 3 = satisfactory, 1 = improvement needed) and justify each grade with specific examples.
• Write down the total number of points and interpret the results (e.g. the Automatic Evaluation and Feedback aspect scores 37 points and falls into the “satisfactory” category).
• Based on the analysis, formulate a recommendation: whether and how this aspect of AI should be integrated into higher education, and you will lead this discussion in one of the following activities.
• You will create the analysis (up to 800 words) within the activity Short Report Writing and receive feedback from the instructor, and then publish it in the folder Mutual Report Sharing with Other Groups so that other groups can see it.
• This is followed by a live discussion as part of the videoconference activity Discussion at the All Participants Level on the Topics.