Evaluation Methods

Poor Evaluation Questions
Poor evaluation questions are too vague, require unavailable or unobservable data, not answerable and are too broad. Such questions can make it impossible for practitioners to identify the critical issue addressed by the project. Without accurate, well-developed and relevant evaluation questions that can establish a viable nexus with stakeholders to the problem, the problem cannot address the issue appropriately.
For example:
How often and how much time do the workers spend working on the project on a daily bases? (This is a double barred question. It addresses two issues concurrently.)
Evaluation Performance
Based on the case study, there some preliminary considerations one ought to take into account when preparing to evaluate performance. It is essential to collect the views of all stakeholders before conducting the evaluation. Such a move will assist in apprehending possible questions and viable answers. Besides, it is essential to have a clear understanding of the methodology to be used. This will involve determining parameters of measurements that will adequately address the questions raised by stakeholders. Such questions will also provide a clue on whether the program is bound to give a solution to the current situation or not. Involve external evaluators who will reduce the aspect of biases that might cause subjective decisions.
Diagnostic Assessment Measurement
By applying this assessment measurement, Tina can identify the skills and knowledge gained by the students and their level of proficiency. Diagnostic assessment helps to measure the current misconceptions held by the students or teachers regarding the K-12 laptop program. Tina can use a diagnostic assessment to determine the student’s progress in terms of concept comprehension related to class assignments and learning. Diagnostic assessment measurement can also be used in a workplace environment. A diagnostic study can be conducted to determine whether there is a skill mismatch in the organization.

Ertmer, P. A., Quinn, J. A., & Glazewski, K. D. (2017). The ID casebook: Case studies in instructional design. Routledge.
Van der Kleij, F. M., Vermeulen, J. A., Schildkamp, K., & Eggen, T. J. (2015). Integrating data- based decision making, assessment for learning and diagnostic testing in formative assessment. Assessment in Education: Principles, Policy & Practice, 22(3), 324-343.

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