Open AccessAn internal evaluation of higher education curriculum using data transformation model
Author(s) -
Michael B. Cahapay
Publication year - 2020
Publication title -
international journal of assessment and evaluation in education
Language(s) - English
Resource type - Journals
eISSN - 2600-870X
pISSN - 2232-1926
DOI - 10.37134/ajatel.vol10.2.1.2020
Subject(s) - curriculum , transformative learning , formative assessment , computer science , perspective (graphical) , curriculum theory , triangulation , transformation (genetics) , work (physics) , emergent curriculum , curriculum mapping , mathematics education , sociology , curriculum development , pedagogy , psychology , artificial intelligence , engineering , mathematics , mechanical engineering , biochemistry , chemistry , geometry , gene
A curriculum does not exist in a void; internal members play a key role in responding to the different forces that continually shape it. One of the approaches to evaluation is through internal evaluation from the perspective of the inside members who work with the curriculum. However, the internal evaluation may pose restricted evaluation due to the innate subjective human judgment. Considering these contexts, this paper performed a pilot internal evaluation of a selected aspect of a higher education curriculum using a triangulation mixed method design called the data transformation model. Based on the results, the evaluation using the data transformation model probed important points of agreement and discrepancy in the data sets. The implications for evaluation theory and curriculum practice are discussed. It is suggested that an extension of the current formative internal evaluation continuing the tradition of data transformative model but progressively focusing on larger aspects of the curriculum should be further conducted.