Jim and David talk about games and the future of education.

Originally posted 2008-03-29 11:03:35. Republished by Blog Post Promoter

Final examinations reflect an antiquated and largely discredited theory of learning, which equates knowledge with factual recall. By discouraging exams, then, Harvard is hardly forsaking academic rigor. Instead, it’s clearing the way for a more engaging, challenging, and truly educative college experience.

The recent Gee/Shaffer essay on Looking Where the Light is Bad make the same point–and even goes further…

Intellectual Property is a critical component of our present and future success in the global economy. The UK’s economic competitiveness is increasingly driven by knowledge-based industries, especially in manufacturing, science-based sectors and the creative industries.

According to some sources, nearly half of the GDP of the United States is based on intellectual property.

The report focuses on copyright issues, and clearly and appropriate policy for protection of intellectual proprety (that also doesn’t constrain the development of new intellectual property!) is critical in a knowledge economy. But so are the processes that lead to the generation of new ideas: innovation and creativity.

Originally posted 2006-12-10 10:26:27. Republished by Blog Post Promoter

In computer games, students can learn by solving problems that are realistic, complex, and meaningful. So games have great potential to teach the kind of thinking that young people need in the digital age, says educational psychology professor David Williamson Shaffer. But after years of designing and testing digital learning environments emphasizing learning in action, Shaffer has turned to the problem of assessment. Shaffer’s research is housed in the Wisconsin Center for Education Research.

Originally posted 2009-06-03 03:37:32. Republished by Blog Post Promoter

This time, the problem is something that a new study calls the N-Effect, which shows that having more competitors lowers test scores.

The abstract is below the jump, but the conclusion is clear: standardized test scores are anything but standard. Even something as simple as the number of other people in the room while you are taking the test can affect your score.

In other words, context matters. And if we want to know what people really can do–how they can solve complex problems, and think about things that matter in the world, we need new ways of thinking about learning and about assessment.

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The paper is The N-Effect: More Competitors, Less Competition, by Stephen M. Garcia, University of Michigan and Avishalom Tor, University of Haifa – Faculty of Law

The discovery that increasing the number of competitors (N) can decrease competitive motivation. Studies 1a-b found evidence that average test scores (e.g., SAT scores) fall as the average number of test-takers at test-taking venues increases. Study 2 found that individuals trying to finish an easy quiz among the top 20 percent in terms of speed finished significantly faster if they believed they were competing in a pool of 10 versus 100 other people. Using a social comparison orientation (SCO) scale, Study 3 showed the N-Effect occurs strongly among those high in SCO and weakly among those low in SCO. Study 4 directly linked the N-Effect to social comparison, ruling out the “ratio-bias” and finding that social comparison becomes less important as N increases. Finally, Study 5 found the N-Effect is mediated by social comparison. Limitations, future directions, and implications are discussed.

Originally posted 2009-10-11 21:05:07. Republished by Blog Post Promoter

http://www.wcer.wisc.edu/publications/workingPapers/Working_Paper_No_2010_10.php

As bloggers and mobile phone eyewitnesses increasingly supplement the “news,” understanding how professional journalists develop their expertise is more important than ever. This paper examines the learning processes within an intermediate-level reporting practicum course. Using epistemic network analysis, the authors explore emergent relationships within developing journalistic expertise. Understanding these relationships should be useful for journalism education as well as the design of research on learning environments.

http://epistemicgames.org/eg/wp-content/uploads/graesser-mcnamara-081709.pdf

The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework.

http://epistemicgames.org/eg/wp-content/uploads/graesser-Harris-Graham-011010.pdf

Intelligent Tutoring Systems (ITS) are computerized learning environments that incorporate computational models in the cognitive sciences, learning sciences, computational linguistics, artificial intelligence, mathematics, and other fields that develop intelligent systems that are well-specified computationally. An ITS tracks the psychological states of learners in fine detail, a process called student modelling. The psychological states may include subject matter knowledge, skills, strategies, motivation, emotions, and other student attributes. An ITS adaptively responds with activities that are both sensitive to these states and that advance the instructional agenda. The interaction between student and computer evolves in a flexible fashion that caters to the constraints of both the student and the instructional agenda. This is a marked departure from a book or a lecture, which unfold in a rigid linear order and are not tailored to individual students.

http://epistemicgames.org/eg/wp-content/uploads/Graesser-handbook-tutoring-110109.pdf

Tutoring is the typical solution that students, parents, teachers, principles and school systems turn to when the students are not achieving expected grades and educational standards. There are serious worries in the community when a school is not meeting the standards of a high stakes test, and teachers are anxious about the prospects of losing their jobs due to the criteria and policies of No Child Left Behind. Schools and families worry when a student runs the risk of losing a scholarship or when an athlete may be cut from a team. Tutors step in to help under these conditions. Wealthier families might end up paying $200 per hour for an accomplished tutor to rescue save a son or daughter. However, these expectations may be rather high, considering that most tutors are same-age peers of the students, slightly older cross-age tutors, citizens in the community, and paraprofessionals who have had little or no training on tutoring pedagogy. Nevertheless, their tutoring can be effective in helping students learn, as we will document in this chapter.

http://epistemicgames.org/eg/wp-content/uploads/graesser-handbook-GDC-Mayer-Alexander-010810.pdf

This chapter reviews research on human tutoring, a form of one-on-one instruction between a tutor and a tutee. In most cases the tutor is knowledgeable about the subject matter and helps the tutee (i.e., the student) improve mastery of the knowledge base or skill. However, sometimes the tutor is a peer of the tutee who plays the role of a tutor, even though the tutor and tutee are at approximately the same level of subject matter mastery. The hope is that the tutorial session is tailored to the needs of the individual student by building on what the student already knows, filling in gaps in knowledge, and correcting conceptual errors. We distinguish between tutors and mentors, although the distinction is not entirely clear-cut. A tutor typically is an expert on a particular subject matter and has a tight control over the tutorial session — turn by turn and moment by moment. In contrast, a mentor has a broader repertoire of knowledge, skills, and wisdom, with only occasional suggestions to the student as the student proceeds with a more self-regulated agenda.