The present study discusses findings that replicate and extend the original work of Burns and Vollmeyer (2002), which showed that performance in problem solving tasks was more accurate when people were engaged in a non-specific goal than in a specific goal. The main innovation here was to examine the goal specificity effect under both observation-based and conventional action-based learning conditions. The findings show that goal specificity affects the accuracy of problem solving in the same way, both when the learning stage of the task is observationbased and when it is action-based. Additionally, the findings show that, when instructions do not promote goal specificity, observation-based problem solving is as effective as action-based problem solving. 2 Keywords: Problem solving; Skill acquisition and learning; Observation vs. intervention

Progress towards understanding human behavior has been hindered by discipline-bound theories, dividing our efforts. Fortunately, these separate endeavors are converging and can be effectively integrated. Focusing on the fundamental features of Picoeconomics, Expectancy, Cumulative Prospect Theory, and Need Theory, Temporal Motivational Theory (TMT) is constructed. TMT appears consistent with the major findings from many other investigations, including psychobiology. Potential applications of TMT are numerous, including: consumer behavior, aggression, stock market, and governmental behavior.

The role of action has been strongly emphasized, not only in cognitive research on learning and problem solving, but also in education and instructional psychology. The Constructivism tradition has long asserted that action plays a crucial role for learners in constructing their own knowledge. In an educational context, active engagement entails students examining their own ideas, considering alternative explanations for newly taught concepts, and evaluating competing perspectives. Some theorists (e.g., Anzai & Simon, 1979) propose that these processes are found when learning is by doing. However, a constructivist perspective implies that instructional formats enable self-monitoring (e.g., Covington, 2000; Pintrich & De Groot, 1990), which includes reflective activities such as describing, explaining, and evaluative thinking (e.g., Covington, 2000; Zimmerman, 1990), which are not exclusive to action. The present article discusses findings that concern two related and thus far, unexplored two questions: How affective is observation-based learning in a complex skill learning task that usually requires processes that involve active engagement with it? How does monitoring affect the transfer of problem solving ability in complex skill learning task? The first aim of the article is to introduce ways of using common educational tools like the self-observation technique, which involves re-exposing individuals to their own self-generated behaviors, in novel ways that can provides insight into how people use self-regulatory mechanisms like monitoring on internally represented behaviors. The second aim is provide support for the view that in the absence of active learning, learning indirectly (i.e. Observation-based learning) is a practical and in some cases necessary method of knowledge and skill acquisition, and does not in turn lead to decrements in acquired knowledge and skill. Finally, the article presents the argument that the degree of self-monitoring that takes place may be a mediating factor in preserving the view that action has a special status in knowledge acquisition.

Information technology (IT) is fundamentally altering the way in which healthcare is delivered to consumers, and offers the promise of improving patient safety, reducing medical errors, improving efficiency, and increasing the reach of health delivery programs. The aim of this research is to examine the factors affecting the adoption and post-adoption of a significant IT innovation in healthcare: online health intervention programs that provide technology-mediated guidance and aid individuals in self-managing their health care. A key challenge confronting health program providers is that of motivating initial enrollment and subsequent continued participation in these interventions. Limited prior work in the information systems and health informatics literature has examined the uptake of technology-mediated health intervention programs. Using data from an online healthcare portal site, this study proposes and empirically tests relationships between the determinants and participation in online health intervention programs.

In problem solving research insights into the relationship between monitoring and control in the transfer of complex skills remain impoverished. To address this, in four experiments participants solved two complex control tasks that were identical in structure but varied in presentation format. Participants learnt either to solve the second task, based on their original learning phase from the first task, or learnt to solve the second task, based on another participant’s learning phase. Experiment 1 showed that, under conditions in which participants ’ learning phase was experienced twice, performance deteriorated in the second task. In contrast, when the learning phases in the first and second tasks differed, performance improved in the second task. Experiment 2 introduced instructional manipulations that induced the same response patterns as Experiment 1. In Experiment 3 further manipulations were introduced that biased the way participants evaluated the learning phase in the second task. In Experiment 4, judgments of self-efficacy were shown to track control performance. The implications of these findings for theories of complex skill acquisition are discussed.

Complex dynamic control tasks (CDC tasks) are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research (Economics, Engineering, Ergonomics, Human Computer Interaction (HCI), Management, Psychology), which remain largely disconnected from each other. The objective of this article is to review theoretical developments and empirical work on CDC tasks, and to introduce a novel framework (Monitoring and Control framework) as a tool for integrating theory and findings. The main thesis of the Monitoring and Control framework is that CDC tasks are characteristically uncertain environments, and subjective judgments of uncertainty guide the way in which monitoring and control behaviors attempt to reduce it. The article concludes by discussing new insights into continuing debates and future directions for research on CDC tasks.

Correspondence concerning this article may be addressed to Anirban Mukhopadhyay, Graduate

Copyright c○2010 by the authors. Communications of the Association for Information Systems

Prior computer-mediated group idea generation research has concluded that social loafing is likely an important factor in reducing individual and group task performance. Group researchers—both focusing on non-technology and technology-mediated groups—have theorized that loafing could be minimized if individuals and groups were given either clear feedback on their task performance or if given clear and attainable performance goals. To examine the efficacy of these interventions on task performance, a computer-mediated idea generation environment was constructed that provided performance feedback for all group members where each member could view how many ideas every group member produced throughout an experimental session. In addition, this environment supported the ability to set a challenging, but attainable, performance goal for each group member (i.e., throughout a session, each member was able to track their performance

The present study compared the accuracy of cue-outcome knowledge gained during prediction-based and control-based learning in stable and unstable dynamic environments. Participants either learnt to make cue-interventions in order to control an outcome, or learnt to predict the outcome from observing changes to the cue values. Study 1 (N = 60) revealed that in tests of control, after a short period of familiarization, performance of Predictors was equivalent to Controllers. Study 2 (N = 28) showed that Controllers showed equivalent task knowledge when to compared to Predictors. Though both Controllers and Predictors showed good performance at test, overall Controllers showed an advantage. The cue-outcome knowledge acquired during learning was sufficiently flexible to enable successful transfer to tests of control and prediction.