PROFILING INNOVATIVE BEHAVIOUR LEVELS AMONG POLYTECHNICS ENGINEERING STUDENTS USING RASCH MEASUREMENT
DOI:
https://doi.org/10.35631/IJMOE.831102Keywords:
Engineering Education, Innovative Behaviour, Performance Assessment, Rasch Measurement, TVETAbstract
Final-year engineering projects offer opportunities to observe how students recognise problems, develop ideas, and put solutions into practice. This study profiled innovative behaviour among 153 final-year diploma students from three Malaysian Premier Polytechnics, representing Civil, Electrical, and Mechanical Engineering. Students were assessed using the previously developed and validated 26-item Innovative Behaviour Assessment Rubric. Rasch person measures were used to describe overall performance, construct sample-referenced profiles, and examine differences by gender, department, and polytechnic. The mean person measure was 0.02 logits (SD = 2.88). Person reliability was 0.95 and separation was 4.55, indicating approximately six distinguishable ability strata. Using predefined z-score boundaries of ±0.5, 49 students (32.0%) were classified as High, 54 (35.3%) as Moderate, and 50 (32.7%) as Low. The distribution was therefore relatively balanced, with a slightly larger Moderate group. A sensitivity analysis using ±1.0 boundaries placed more students in the Moderate category, showing that the profiles depended on the classification rule. On the common 26-item Wright Map, several of the most difficult criteria concerned advanced problem recognition, particularly the clarification and justification of project objectives. Several implementation criteria were less difficult. Subgroup tests detected no statistically significant differences by gender, department, or polytechnic; these results do not establish equivalence between groups. The findings identify specific behaviours that may warrant closer attention during project supervision, especially problem framing and objective refinement. The profiles can inform formative feedback and curriculum planning, provided that High, Moderate, and Low are interpreted relative to this sample rather than as externally established proficiency standards.
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