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AI: Use Cases for Exams

Specific Use Cases for the Application of Generative AI in Exams

KI-generiert

Specific Use Cases for the Application of Generative AI in Exams

Please note the legal notices and the “two-examiner principle” regarding the automatic generation of actual exam content! See https://digitale-lehre.uni-siegen.de/empfehlungen-fuer-die-nutzung-von-ki-basierten-anwendungen-an-der-uni-siegen/ 

Automatic Generation of Quizzes and Exam Questions

AI can automatically generate quiz questions or exam questions. To take into account the specific course material, additional documents from the relevant department, course, etc., can (and should, if necessary) be provided by first uploading them to the respective AI tool.

The following prompts can be used as a basis for creating exam questions in various subject areas. In doing so, the underlying learning/teaching paradigm of constructive alignment should always be taken into account:

Prompt for basic retrieval of factual knowledge 
For creating questions that test factual knowledge.
“Generate [number] questions in [subject area] that test recall of key terms and facts related to [topic].”
Ref: Anderson & Krathwohl (2001). A taxonomy for learning, teaching, and assessing.

Comprehension prompt
For questions that test understanding of concepts.
“Generate [number] questions that ask students to explain [concept] in the context of [subject area] in their own words.”
Ref: Biggs & Tang (2011). Teaching for Quality Learning at University.
Application- and analysis-level prompts

Application prompt
For scenario-based questions that require the application of knowledge.
“Create [number] case scenarios in [field of study] in which students apply [theory] to solve realistic problems.”
Ref: Biggs (1996). Enhancing teaching through constructive alignment.

Analysis prompt
For questions that require a breakdown of information.
“Design [number] questions that ask students to analyze relationships between components of [complex topic] in [subject area].”
Ref: Bloom et al. (1956). Taxonomy of Educational Objectives.

Evaluation Prompt
For assignments involving critical evaluation.
“Create [number] assignments that ask students to critically evaluate [theory/method] based on established criteria in [field of study].”
Ref: Biggs & Collis (1982). Evaluating the Quality of Learning: The SOLO Taxonomy.

Creation prompt
For assignments that require original work.
“Design an exam question in which students must create an original [product/solution] that addresses [problem] in [field of study].”
Ref: Shreeve et al. (2010). Constructive alignment and student creativity.
Prompts for Multi-Level Assessment

Prompt for integrated assessment
For comprehensive assignments that span multiple cognitive levels.
“Create a multi-part exam assignment in [field] that progresses from identifying [concept] to applying it in [context] to evaluating [related topic].”
Ref: Trigwell & Prosser (2014). Qualitative variation in constructive alignment in curriculum design.

Prompt for authentic assessment
For tasks with real-world applications.
“Design a realistic scenario in [subject area] in which students must demonstrate [list of skills] as practitioners in the professional field would.”
Ref: Gulikers et al. (2004). A five-dimensional framework for authentic assessment.

Prompt for Subject-Specific Thinking
For discipline-specific thinking processes.
“Generate questions that assess how students apply [discipline]-specific approaches to [topic].”
Ref: Jervis & Jervis (2005). What is the constructivism in constructive alignment?

Prompt for Professional Skills
For assessing career-relevant skills.
“Create tasks that measure students’ competence in [professional skill] within a [disciplinary context].”
Ref: Knight (2001). Reconstructing Assessment for Learning in Higher Education.

Suppose you are teaching a course on cognitive psychology with a focus on memory models. Here is a concrete example of how you can use the Constructive Alignment prompts:

Step 1: Define the learning objectives

Your students should:

Be familiar with various memory models
Understand the differences between these models
Be able to apply the models to everyday memory phenomena
Be able to critically evaluate research methods for studying memory
 

Step 2: Applying the prompts to different levels of testing

Knowledge Level (Basic Recall Prompt):

Create 5 questions in cognitive psychology that test recall of key terms and facts related to multistore memory models.

Sample Answer:
Name the three main components of the multistore model according to Atkinson and Shiffrin.
Define the term “sensory memory” according to the multistore model.
What is the maximum duration of storage attributed to short-term memory in the classical multistore model?
Name two forms of encoding that typically occur in long-term memory.
Describe the process of consolidation as it relates to memory.


Comprehension Prompt:

Generate 3 questions that prompt students to explain Baddeley’s working memory model in the context of cognitive psychology in their own words.

Sample Result:
Explain how Baddeley’s working memory model differs from classical short-term memory in the multi-store model.
Describe the role of the phonological loop and explain how it can be experimentally demonstrated.
Explain the function of the central executive and its importance for working memory.
 

Application Prompt:

Create two case scenarios in cognitive psychology in which students apply memory models to solve realistic problems.

Sample Answer:
An elementary school teacher notices that her students are having difficulty memorizing new vocabulary words. Apply Baddeley’s working memory model to explain which cognitive processes are involved, and develop three concrete, theory-based strategies to improve vocabulary learning.
A neuropsychologist is examining a patient with amnesia following an accident. The patient can recall events prior to the accident but is unable to form new memories. Use Squire’s long-term memory model to explain this phenomenon. Which memory systems might be intact, and which might be impaired?
 

Analysis Prompt:

Design two questions that prompt students to analyze relationships between different memory models in cognitive psychology.

Sample Result:
Analyze the conceptual overlaps and differences between the Levels of Processing model by Craik and Lockhart and the Multistore Model. To what extent do these models complement or contradict each other?
Compare Baddeley’s working memory model with Sweller’s Cognitive Load Theory. Analyze how both theories contribute to explaining learning processes and cognitive overload.
 

Evaluation Prompt:

Create an assignment that asks students to critically evaluate research methods used to study memory.

Sample Result:
Select two of the following experimental paradigms for memory research: a) word list recall, b) directed forgetting, c) false memory paradigm, d) working memory span tasks.
Critically evaluate the strengths and weaknesses of the selected methods with regard to:
Ecological validity
Construct validity (do they actually measure the intended memory processes?)
Methodological issues
Generalizability to real-world memory phenomena
Refer to at least two empirical studies per method and develop suggestions for methodological improvement.
 

Creation Prompt:

Design an exam question in which students must create an original research design that investigates a memory phenomenon in cognitive psychology.

Sample Answer:
Develop a complete experimental research design to investigate one of the following memory phenomena:
The generation effect (self-generated information is better remembered)
Context-dependent memory
Prospective memory in everyday life
Your research design should include the following elements:
Theoretical background with reference to relevant memory models
Specific research question and hypotheses
Detailed methodological approach (sample, materials, procedure)
Proposed methods of analysis
Discussion of possible results and their theoretical implications
Critical reflection on methodological strengths and weaknesses

AI in Exams - Share Your Experiences with AI

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Have you developed helpful prompts for teaching? Send us your ideas, give us feedback on existing examples, and inspire other educators. Feel free to contact us at

digitale-lehre@uni-siegen.de