The impact of hybrid classroom/distance education approaches is examined in the context of the case method. Four distinct semester-long treatments, which varied mixes of classroom and online discussion, were used to teach a graduate MIS survey course. Specific findings suggest that by using Web technology, college instructors may offer students the option of participating in high-quality courses using the case method pedagogy in an online environment. Students not only appear to do as well as in the traditional classroom, but the data suggest that students in the online environment may perform better at multiple levels of learning outcomes, especially when using a blend of classroom and online technologies. Furthermore, the precepts of the case method pedagogy may be enhanced by the use of online discussions. Instructors employing the technique may find their own importance devalued, while the time demands of the approach can be much greater than for traditional classes. The findings infer that it is the model of learning and its fit with supporting technologies, rather than the presence of technology per se, which enhances learning outcomes.
When looking for advice, is it better to seek guidance from an expert or from others more like yourself? The paper introduces a simulation model in which a client seeks advice on how to improve fitness. Its focus is on comparing the outcomes of taking guidance from self-similar peers (homophily) and experts who base their recommendations on statistical significance.The simulation places a collection of agents on a fitness landscape and models the informing process as the agents search for higher fitness. Four distinct agent types are developed: 1) randomized hill climbing agents take no advice and search for higher fitness by testing adjacent states and serve as the control case, 2) imitative agents look for guidance from nearby agents (mimicking homophily), 3) expert-guided agents are advised based upon a statistically-derived view of the landscape, and 4) goal-setting agents establish goals based upon observing other clients and then steadfastly pursue those goals regardless of intervening fitness levels. Of particular interest is how well each type of agent performs as the complexity of the underlying landscape varies.The simulations described produce strikingly clear outcomes that parallel behaviors observed in real-world settings. In low-complexity environments, expert-guided agents match or outperform all other agent types. As complexity grows, however, expertise becomes fragile to the point where it can become worse than no guidance at all. Imitative agents and goal-setting agentsboth of which engage in homophilic behaviors by design-track together until substantial levels of complexity are reached, at which point the goal-setting agents outperform all other agent types.These results are important in two ways. First, they suggest an underlying rationale for the widely observed homophilic proclivities of human beings-provided we make the assumption that complex environments are routinely encountered. Second, they offer an explanation as to why practitioners frequently seem indifferent to the advice of expert research in fields-such as business and education-where the landscapes being investigated are intrinsically complex.
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