Measuring the effectiveness of online problem solving for improving academic performance in a probability course

Research on impact in student achievement of online homework systems compared to traditional methods is ambivalent. Methodological issues in the study design, besides of technological diversity, can account for this uncertainty. Hypothesis This study aims to estimate the effect size of homework practice with exercises automatically provided by the ‘e-status’ platform, in students from five Engineering programs. Instead of comparing students using the platform with others not using it, we distributed the subject topics into two blocks, and created nine probability problems for each block. After that, the students were randomly assigned to one block and could solve the related exercises through e-status. Teachers and evaluators were masked to the assignation. Five weeks after the assignment, all students answered a written test with questions regarding all topics. The study outcome was the difference between both blocks’ scores obtained from the test. The two groups comprised 163 and 166 students. Of these, 103 and 107 respectively attended the test, while the remainder were imputed with 0. Those assigned to the first block obtained an average outcome of −1.85, while the average in the second block was −3.29 (95% confidence interval of difference, −2.46 to −0.43). During the period in which they had access to the platform before the test, the average total time spent solving problems was less than three hours. Our findings provide evidence that a small amount of active online work can positively impact on student performance.

Resource competition and technological diversity

The work develops and investigates a mathematical model for evolution of the technological structure of an economic system where different technologies compete for the common essential resources. The model is represented by a system of consumer–resource rate equations. Consumers are technologies formalized as populations of weakly differentiated firms producing a similar commodity with like average output. Firms are characterized by the Leontief–Liebig production function in stock-flow representation. Firms self-replicate with a rate proportional to production output of the respective technology and dissolve with a constant rate of decay. The resources are supplied to the system from outside and consumed by concerned technologies; the unutilized resource amounts are removed elsewhere. The inverse of a per firm break-even resource availability is proposed to serve as a measure for competitiveness towards a given resource. The necessary conditions for coexistence of different technologies are derived, according to which each contender must be a superior competitor for one specific resource and an inferior competitor for the others. The model yields a version of the principle of competitive exclusion: in a steady state, the number of competing technologies cannot exceed the number of limiting resources. Competitive outcomes (either dominance or coexistence) in the general system of multiple technologies feeding on multiple essential resources are shown to be predictable from knowledge of the resource-dependent consumption and growth rates of each technological population taken alone. The proposed model of exploitative competition with explicit resource dynamics enables more profound insight into the patterns of technological change as opposed to conventional mainstream models of innovation diffusion.

A Technique for Improving the Precision of the Direct Measurement of Junction Temperature in Power Light-Emitting Diodes

Extending the lifetime of power light-emitting diodes (LEDs) is achievable if proper control methods are implemented to reduce the side effects of an excessive junction temperature, TJ. The accuracy of state-of-the-art LED junction temperature monitoring techniques is negatively affected by several factors, such as the use of external sensors, calibration procedures, devices aging, and technological diversity among samples with the same part number. Here, a novel method is proposed, indeed based on the well-known technique consisting in tracking the LED forward voltage drop when a fixed forward current is imposed but exploiting the voltage variation with respect to room temperature. This method, which limits the effects of sample heterogeneity, is applied to a set of ten commercial devices. The method led to an effective reduction of the measurement error, which was below 1 °C.

The Impact of Technological Capability on Financial Performance in the Semiconductor Industry

The modern semiconductor industry is going through rapid changes as new markets and technologies appear. In this paper, such technology-intensive firms’ relationship between technological capability and financial performance is analyzed with regression analysis. Revenue and market capitalization are used as dependent variables. For the independent variables, the technological intensity, technological diversity, technological asset, and technological efficiency are used. The analysis results revealed different effects of technological capability on financial performance. Also, regression analysis is conducted by dividing firms into high and low groups based on technological asset and technological efficiency, and the analysis result revealed different effects of technological intensity and technological diversity on financial performance. For technological asset, the financial performance in the high group is affected more by technological intensity, and the financial performance in the low group is affected more by technological diversity. For technological efficiency, only the financial performance in the high group is affected by technological intensity. Although both groups’ financial performance is somewhat affected by technological diversity, there was no statistically significant differences between the groups. By separating the effect of technological capability on financial performance, this research can provide more detailed analysis results compared to previous literature and the methods of managing technological capability for semiconductor firms.