Integrating technology and non-routine problems: the design, development, and validation of a computer-aided assessment for non-routine problem-solving - Molina, Marivic G.; Yabut, Erna V. (Universitas Terbuka, 2025)
The increasing demand for higher-order thinking skills in 21st-century education underscores the need for innovative resources, as traditional materials often focus on routine problems with limited opportunities for non-routine problem-solving. This study designed, developed, and validated a computer-aided assessment for non-routine problem-solving using the Design and Development Research method, conducted in three phases: needs analysis, design and development, and evaluation. Data collection included a literature review, systematic design and development, expert validation, and user feedback, analyzed through descriptive statistics and thematic analysis. Findings show that the computer-aided assessment supports non-routine problem-solving and addresses limitations of traditional assessments. The needs analysis identified gaps in current methodologies and the benefits of technology-enhanced assessments. The design and development phase produced an assessment promoting cognitive engagement, while the evaluation phase gathered expert validation and user feedback. Five experts in information technology and mathematics education provided positive evaluations of the assessment’s functionality, accessibility, and cognitive support. Feedback from 15 students across three educational institutions indicated enhanced engagement, independent learning, and deeper mathematical understanding. Although minor technical issues were noted, they did not significantly impact the computer-aided assessment’s quality. The validated computer-aided assessment shows potential as a digital tool for fostering non-routine problem-solving and interactive learning. It suggests that computer-aided assessments with non-routine problems may enhance higher-order thinking skills by promoting cognitive engagement and personalized learning. Future research could explore its long-term impact, adaptability across disciplines, and potential for adaptive learning and collaborative features to maximize educational effectiveness.