Massive open online courses (MOOC) transcends the time and space limits of traditional classroom teaching, and promotes the sharing of teaching resources. However, the effect of this emerging teaching mode is yet to be determined. In this paper, the big data analysis is introduced to evaluate the MOOC teaching quality. Taking several online courses as an example, a video player was de-signed to compute the learning time using the Hadoop platform. On this basis, the author constructed a teaching quality evaluation platform. In addition, the learning cost coefficient was calculated by the naive Bayesian model, and the evaluation results were analysed in details. The research findings shed practical new light on the evaluation of MOOC teaching quality.
It is well documented that people are reluctant to switch from a default option. We experimentally test the robustness of this behavioral inertia in a collective decision-making setting by varying the default option type and the decision-making environment. We examine the impacts of automatic-participation and no-participation default options on subjects' participation in a public goods provision and their contributions. Two variants of public goods game are employed: the linear and the threshold public goods games. The study shows the evidence of partial stickiness rather than complete stickiness of default options as indicated in empirical studies. Our experimental results square with the evidence of behavioral inertia only when the automatic-participation default is used. This default boosts contributions in the linear public goods game but not in the threshold public goods game. The evidence We thank Tim Cason, David Gill, Dan Houser, Juanjuan Meng, Andreas Ortmann, the editors, two anonymous referees and seminar participants at NTU, the International Meeting of the Economic Science Association (ESA) at New York University, the Australian Conference of Economists (ACE) in Melbourne, the Econometric Society North American Meeting at the University of Southern California, and the Asian Meeting of the Econometric Society at the National University of Singapore for their useful comments.
Electronic supplementary materialThe online version of this article (doi:10.1007/s00355-017-1036-x) contains supplementary material, which is available to authorized users.
Students with little professional software development experience typically have low intrinsic motivation and beyond achieving a good grade, low extrinsic motivation to study and appreciate the value of software engineering curricula. Unlike other subjects, introductory software engineering instructors exert a great deal of effort justifying and motivating their course topics. Since 2006 the University of Hawaii has been developing a series of "early awareness" engagements within an introductory Systems Analysis and Design course designed to foster intrinsic and extrinsic motivation and orient students to value learning software engineering. Measuring motivation and perceived value is difficult, but there are key indicators to determine the impact of our improvements such as higher course evaluations, greater class attendance, and increased positive feedback from students and employers. Our results show that these key indicators have improved since introducing early engagements. Furthermore, students like this approach, value the course more, do better quality work, and evaluate the course more positively. Longitudinal follow-ups indicate greater interest and success in pursuing software engineering related careers. This paper shares the details of our early awareness engagements, how they are applied in the classroom, some of our experiences in using them, and evidence that they have a positive impact. Our goal is to provide specific and practical means that instructors can use immediately to improve the perceived value of software engineering for novice students prior to or while they study it.
We experimentally investigate the role of information transparency for equilibrium selection in stag hunt coordination games. These games can be transformed from a prisoner's dilemma game by introducing a centralized reward or punishment scheme. We aim to explore the impact of the disclosure of information on how final payoffs are derived on players' incentive to coordinate on the payoff-dominant equilibrium. We find that such information disclosure significantly increases the tendency of players to play payoff-dominant action and reduces the occurrence of coordination failure. The mechanism works directly through the positive impact of disclosure on the saliency of the payoffdominant equilibrium, and indirectly through the positive influence of disclosure on players' belief about the likelihood of cooperation by opponent.
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