Foundations of Assessment and Grading in Higher Education

Course Description

Assessment shapes student learning, communicates academic standards, and requires well-founded professional judgment. At the same time, designing and grading assessments is one of the most complex and sensitive responsibilities in university teaching.

This introductory blended-learning workshop provides a research-informed foundation for high-quality assessment and grading practices. Participants explore assessment within the framework of constructive alignment and examine key quality criteria such as validity, reliability, fairness, and transparency. Special attention is given to grading as a critical sub-process that significantly influences the overall quality and defensibility of assessment decisions.

The workshop addresses cognitive biases in grading and introduces practical strategies to enhance objectivity and consistency. Participants develop and refine scoring guides and rubrics for their own assessment formats and discuss how to handle challenging situations such as group work, peer assessment, or oral examinations.

The course also reflects on the implications of generative AI for assessment design and academic integrity, supporting participants in adapting their assessment practices to contemporary teaching contexts.

The synchronous session takes place online and is highly interactive. Active participation (including camera use where possible) is expected. Regular breaks are scheduled to support sustained engagement.

Learning outcomes

After completing the workshop, participants will be able to:

• explain and justify the role of assessment within constructive alignment and evaluate the coherence of assessment practices in their own courses,

• apply key quality criteria (validity, reliability, fairness, transparency) to analyse and systematically improve their own assessment formats,

• critically reflect on and revise their grading practices in line with professional standards and institutional regulations,

• analyse potential cognitive biases in grading situations and implement strategies to enhance fairness and reliability,

• design and adapt scoring guides and rubrics for different assessment formats in a transparent and criteria-based manner,

• develop defensible assessment strategies for complex situations (e.g., group work, peer review, oral examinations),

• evaluate the impact of generative AI on assessment design and adapt assessment tasks accordingly.

Participation requirements

• Completion of the asynchronous preparation phase one week prior to the live session

• Willingness to actively participate in discussions and breakout activities

• Participants are encouraged to bring an example of their own assessment format (e.g., exam task, rubric, grading challenge)

Blended Learning Format (8 AE total)

• Asynchronous preparation (3 AE)
  Short input materials and guided analysis of participants’ own assessment formats (alignment, quality criteria, grading risks).

• Interactive online session (4 AE)
  Application-oriented activities including calibration exercises, peer exchange, rubric development, and structured redesign of assessment elements.

• Transfer assignment (1 AE)
  Submission of a revised assessment element or short reflective analysis with individual feedback from the instructor.