“Humor and College Teaching,” by Howard Pollio, , The Teaching of Psychology: Essays in Honor of Wilbert J. McKeachie and Charles L. Brewer, 69-80, http://books.google.com/books?hl=en&lr=&id=6Bp0zsdGTkQC&oi=fnd&pg=PR7&sig=P3wab6vQ4aMT208w2IGKSiEe-7c&dq=%22Humor+and+College+Teaching%22+Howard+Pollio&prev=http://scholar.google.com/scholar%3Fq%3D%2522Humor%2Band%2BCollege%2BTeaching%2522%2BHoward%2BPollio%26hl%3Den%26lr%3D%26safe%3Doff%26sa%3DG.
“Self-Regulated Learning in College Students: Knowledge, Strategies, and Motivation,” by Paul Pintrich and Teresa Garcia, Student Motivation, Cognition, and Learning: Essays in Honor of Wilbert J. McKeachie, 113-133, http://www.amazon.ca/Student-Motivation-Cognition-Learning-McKeachie/dp/0805813764.
“Frames, Biases, and Rational Decision-Making in the Human Brain,” by Benedetto De Martino et al, Science, 4 August 2006, Vol 313 pp 684-687, http://www.sciencemag.org/cgi/content/abstract/313/5787/684.
Articles from both main classes appear below, and it is neat when they overlap. For instance:
In general, students who use more deep-processing strategies like elaboration and organization are more likely to do better in the course in terms of grades on assignment, exams, and papers, as well as overall course grade. In addition, students who attempt to control their cognition and behavior through the use of planning, monitoring, and regulating strategies also do better on these academic performance measures. (Pintrich and Garcia 121)
and in neurobiology:
Our data raise an intriguing possibility that more ‘rational’ individuals have a better and more refined representation of their own emotional biases that enables them to modify their behavior in appropriate circumstances, as for example when such biases might lead to suboptimal decisions.” (De Martino et al 687)
Just as fun is when Evolutionary/Genetic theories invade Educational Psychology outright.
After all, college faculty deal with whole students, not an array of motivational and cognitive constructs. Bereiter (1990) argued that a focus on the individual is too large and not context-specific enough. He suggested the use of “modules” that are “carried” by the individual, thereby allowing for individual differences and avoiding problems of strong contextualism; but at the same time, he noted that these modules are assembled and activated differentially depending on the situation. (Pintrich and Garcia 125)
(hmm… experiential and genetic individuality… hmmm)
The rest of the notes appear below the fold:
In contrast, Bill [McKeachie] has always taken a more cognitive view of learning and as he observed in Teaching Tips, (McKeachie, 1994), “human beings are learning organisms — seeking, organizing, coding, storing, and retrieving information all their lives; building on cognitive structures to continue learning throughout life, (certainly not losing the capacity to learn);; continually weeking meaning” (p. 289) (Pintrich and Garcia 114-115)
First, it has become commonplace in cognitive psychology to note that students’ prior knowledge influences their learning. In some ways, this general principle has probably replaced the law of effect and law of exercise as a basic principle of learning.” (Pintrich and Garcia 118)
Donald (1990, this volume) showed that university faculty do think and reason somewhat differently about the nature of evidence and the logic of argument, depending on their discipline… It appears that students who are less committed to an absolutist view of knowledge (e.g., “there is only one right answer and authorities should tell it to me”) are more likely to be mastery-oriented and use deeper processing strategies (Schutz, Pintrich, and Young 1993)… Most faculty members believe that by teaching the content and methods of their discipline, students will develop the appropriate epistemic beliefs and thinking frames, but Donald’s work (this volume) suggests that this may not be the case.” (Pintrich and Garcia 120)
We believe that one of the major contributions of his work for the field of college student learning is its reliance on a theoretically-based model of the active, constructive learner as well as its focus on the actual cognitive and metacognitive stratgies that students might use when they try to learn and study, rather than generaly learning or personality styles (e.g. introversion-extroversion, field dependend or independence; Myers-Biggs profiles). Much of the research on college student learning has concentrated on these general personality styles and it is not clear how they are linked tos tudents’ actual study behavior or their cognitive processing of lecture and text information. (Pintrich and Garcia 121)
Besides these general substantive findings, a second more practical contribution of this research has been the development of a self-report instrument for assessing learning strategies and motivation, the Motivated Strategies for Learning Questionnaire or MSLQ (Pintrich, Smith, Garcia, & McKeachie, 1993). (Pintrich and Garcia 122)
Traditionally, cognitive research has focused on learners in an experimental setting and not dealt with motivation, thereby portraying a ‘motivationaly inert’ learner.” (Pintrich and Garcia 123)
In contrast, the strategy of defensive pessimism is a pattern in which individuals use anxiety to fuel effort (Norem & Cantor, 1986). Defensive pessimism involves setting unrealistically low expectations that create anxiety; this anxiety is then used to promote greater efforts whose dividends are generally superior performance. (Pintrich and Garcia 126)
As Zimmerman (1989, this volume) and others like Corno (1993) pointed out, students’ ability to control their cognition, motivation, and volition can have a dramatic influence on learning. (Pintrich and Garcia 126)
Theories of decision-making have tended to emphasize the operation of analytic processes in guiding choice beahvior. However, more intuitive or emotional respons. (De Martino et al 684)
We investigated the neurobiological basis of the framing effect by means of functional magnetic resonance imaging (fMRI) and a novel financial decision-making task. Particpants (20 university students or graduates) received a message indicating the mount of money that they would initially receive in that trial (eg, “You receive 50”). Subjects then had to choose between a “sure” option and a “gamble” option presented in the context of two diferent frames. The “sure” option was formulated as either the amount of money retained from the intiial amount (eg keep 20 of the 50; “Gain” frame) or as the mount of money lost from the initial amount (eg lose 30 of the 50; “Lose frame). The “gamble” option was identical in both frames and was represented as a pie chart depicting the probability of winning or losing (Fig 1.) (14) (De Martino et al 684)
Consequently, we could identify brain areas that were more active when subjects chose in according with the frame effect (ie Gsure + Lgamble) as opposed to when their decisions ran counter to their general behavioral tendency (Ggamble + Lsure). (De Martino et al 686)
Using the overall susceptibility of each subject to the frame manipulation as a between-subjects statistical regressor, operationalized as a “rationality index” (14), we found a significant correlation between decreased suscepctibility to the framing effect and enhanced activity in the orbital and medial prefrontal cortex (OMPFC), specifically in the right orbitofrontal cortext and the ventromedial prefrontal cortex. (De Martino et al 686)
Consequently, our findings indicate that frame-related valence information is incorporated into the relative assessment of options to exert control over the apparent risk sensitivity of individual decisions. (De Martino et al 686-687)