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This study aims to focus on providing a computerized classification testing (CCT) system that can easily be embedded as a self-assessment feature into the existing legacy environment of a higher education institution, empowering students with self-assessments to monitor their learning progress and following strict data protection regulations. The purpose of this study is to investigate the use of two different versions (without dashboard vs with dashboard) of the CCT system during the course of a semester; to examine changes in the intended use and perceived usefulness of two different versions (without dashboard vs with dashboard) of the CCT system; and to compare the self-reported confidence levels of two different versions (without dashboard vs with dashboard) of the CCT system.

A total of N = 194 students from a higher education institution in the area of economic and business education participated in the study. The participants were provided access to the CCT system as an opportunity to self-assess their domain knowledge in five areas throughout the semester. An algorithm was implemented to classify learners into master and nonmaster. A total of nine metrics were implemented for classifying the performance of learners. Instruments for collecting co-variates included the study interest questionnaire (Cronbach’s a = 0. 90), the achievement motivation inventory (Cronbach’s a = 0. 94), measures focusing on perceived usefulness and demographic data.

The findings indicate that the students used the CCT system intensively throughout the semester. Students in a cohort with a dashboard available interacted more with the CCT system than students in a cohort without a dashboard. Further, findings showed that students with a dashboard available reported significantly higher confidence levels in the CCT system than participants without a dashboard.

The design of digitally supported learning environments requires valid formative (self-)assessment data to better support the current needs of the learner. While the findings of the current study are limited concerning one study cohort and a limited number of self-assessment areas, the CCT system is being further developed for seamless integration of self-assessment and related feedback to further reveal unforeseen opportunities for future student cohorts.

The purpose of this paper is to present a productivity measure for hospital services in Ontario.

The study applied the Malmquist Productivity Index (MPI) to assess the efficiency of hospital services in Ontario, Canada, over the period 2003‐2006. The MPI was decomposed into efficiency change and technological change. Efficiency change was further decomposed into pure efficiency change and scale efficiency change. A bootstrapping technique was also used to obtain confidence intervals for the output oriented MPI and its decompositions.

By estimating confidence intervals it was found that a large number of hospitals did not achieve significant progress in terms of productivity. By taking geometric means of estimates for all years it was observed that while overall productivity and efficiency of hospitals in Ontario declined during the study period, technological progress increased at a rate of 5.95 percent on average.

The present study helps to understand the productivity and technological change and change in technical efficiency in this vital sector of the economy, which is important for policy making identifying improvement opportunities in resource allocation. It was observed that Ontario hospitals did not improve the efficiency with which they employed their inputs (i.e. staff and supplies) over the study period; they did achieve gains through application of technologies.

The paper provides a thorough study on productivity growth of health care services in Ontario using a non‐parametric framework with bootstrapping. It also provides a robust measurement and analysis of the contributions of technology, size of operation and use of inputs to the performance of hospitals in Ontario.