FREE 30-Minute Turnitin Webcast: The Sources in Student Writing

30-Minute Webcast Series The Sources in Student Writing   DATE:  Thursday, January 17, 2013 TIME:   10:00am PT / 11:00am MT / 12:00 noon CT / 1:00pm ET   View Local Time COST:  Complimentary    PRESENTERS: Jason Chu is the Senior Education Manager at Turnitin. His focus is on working to build resources for educators, and his personal passion is to find better ways to enhance student achievement. He analyzed the statistics from the Turnitin database that is the basis for this webcast. Renee Bangerter is a Professor of English at Saddleback College and has been teaching writing for 15 years. She collaborates with K-12 teachers developing curriculum to bridge the gap between high school and college in reading, writing and grammar. Renee creates the professional development webinars for Turnitin, emphasizing how instructors can innovatively teach students about plagiarism. Summer Dittmer has taught high school Drama, Online Expository Writing, English and Honors English for 11 years. Aside from teaching 12th grade Literature, she is the Student Activities Coordinator at Mercy High School in Burlingame, CA. She has trained teachers in developing online curriculum, along with assisting in implementing effective one-to-one iPad programs.     Webcast Overview Join us as we share updated findings on the types of internet sources that students use in their written work, discuss the implications of the findings and share best practices to help prevent plagiarism in the classroom. View all 30-Minute Webcasts   The 30-Minute Webcast Series from Turnitin is for busy educators who want to stay current with the latest trends and technologies on preserving academic integrity, improving student writing across the curriculum, and promoting student success.

Turnitin is a service of iParadigms, LLC 1111 Broadway, Oakland, CA 94607, USA   |   +1.510.764.7600   |   www.turnitin.com

FREE 30-Minute Turnitin Webcast: The Sources in Student Writing

Tomorrow's Professor: Is Intellectual Curiosity a Strong Predictor for Academic Performance?

http://derekbruff.org/blogs/tomprof/2013/01/14/tp-msg-1219-is-intellectual-curiosity-a-strong-predictor-for-academic-performance/

 

Is Intellectual Curiosity a Strong Predictor for Academic Performance?

 

What Does Research Tell us about Academic Performance and Curiosity?

 

For better or worse, academic performance has long stood as a proxy for general aptitude. To understand what factors affect academic performance gives us a better understanding of how instructors can help students achieve their greatest potential in college. Empirical evidence strongly suggests that academic performance can be predicted by a combination of cognitive ability (or intelligence) and effort. Non-ability personality traits, such as effort, can be potentially more meaningful than intelligence because less able students can compensate for lower levels of cognitive ability by becoming more conscientious, studying harder, and paying greater attention to details and rules. Beyond cognitive ability and effort, researchers look to so-called investment traits to explain inter-individual differences among people?s drive to pursue, enjoy, and engage in learning opportunities. Intellectual curiosity conveniently describes this impulse, as does the researcher?s titular phrase,
the hungry mind.? Like cognitive ability and effort, intellectual curiosity positively associates (at medium effect sizes) with academic performance.

Several instruments have been developed to measure something like curiosity. The ?Need for Cognition? scale measures the ?tendency for an individual to engage in and enjoy thinking? (Cacioppo & Petty, 1982, p. 116). The ?Typical Intellectual Engagement? (TIE) scale was designed to ?differentiate among individuals in their typical expression of a desire to engage and understand their world, their interest in a wide variety of things, and their preference for a complete understanding of a complex topic or problem, a need to know?.? (Goff and Ackerman, 1992, p. 539). Because these measures have similar conceptual underpinnings and share criteria validity for academic performance and intelligence, they appear to measure the same trait dimension, and studies that use these scales can be rolled into a meta-analysis.

 

Study & Methods

To investigate whether curiosity is a strong determinant for academic performance, Von Stumm, Hell, & Chamorro-Premuzic extracted correlation coefficients from three previous studies and performed four meta-analyses that focused on TIE to stand in for curiosity. For the new TIE meta-analyses, the researchers selected 11 studies (including several in which one of the authors had participated). They excluded studies that did not include empirical data, did not include zero-order correlations, or included previously reported data. In these studies, academic performance was expressed as either grade point average or an academic performance composite. From the extracted correlation coefficients and the new meta-analyses, the authors created five path models using a stepwise process, settling on a single, best-fit model.

 

Findings

The best fitting model indicated that intelligence, TIE, and conscientiousness were direct and intercorrelated predictors of academic performance. Within this model, intelligence (.35) accounted for the greatest amount of variance while curiosity (.20) and effort (.20) had slightly smaller and equal and independent impacts on academic performance. (The preceding measurements are standardized beta weights.) The authors thus confirm their hypothesis that intellectual investment, including curiosity, is a key determinant of academic performance.

 

Discussion and Implications

The authors suggest several important ramifications of this finding:

? Academic performance can be increased if students? intellectual curiosity is regularly renewed and stimulated. Thus, students should be

encouraged to follow challenging paths and not be exclusively rewarded for their ?acquiescent application of intelligence and effort.? Universities

and colleges should seek to exploit opportunities to inspire curiosity and reward productive novelty.

? Admissions officers should pay attention to intellectual curiosity as a strong predictor of potential.

? Future studies to examine predictors of academic success should seek to expand their range beyond intelligence and effort.

 

Implications

Technology may have a role in cultivating curiosity by providing greater access to new information, new ways to participate in culture through new media (Jensen et al, 2006), and novel methods of visualizing data. Curiosity might also have a role to play in orienting students toward life-long learning, which has already been shown to be influenced by such pedagogical practices as active learning, reflection, and tasks that encourage perspective-taking (Mayhew, M.J., Wolniak, G.C., & Pascarella, 2008).

 

Study Limitations

As the authors note, the study is constrained by several factors, including the quality of the original studies in the meta-analyses. Further, only conscientiousness was used as a proxy for effort, ignoring academic motivation, self-efficacy, and ambition. The study also did not consider the cumulative effect of success as an ongoing magnifier for conscientiousness and curiosity. To correct for this, another study would have to consider the longitudinal effects of an academic course of study and not a single moment. Finally, the authors concede that despite the encouraging results that showed that conscientiousness and intellectual curiosity combined influenced academic performance to the same degree as intelligence, other variables likely to have an effect, such as choice of subject, socio-economic status, self-confidence, etc., were not factored into a final model. Seen in the context of these limitations, the study directs researchers to continue to explore the nexus of no

 n-ability personality traits with intelligence to predict academic performance.

 

References

Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42, 116-131.

Goff, M., & Ackerman, P. (1992). Personality-intelligence relations: Assessment of typical intellectual engagement. Journal of Educational Psychology, 84, 537-552.

Jenkins, H., Clinton, K., Purushotma, R., Robison, A. J., & Weigel, M. (2006). Confronting the challenges of participatory culture: Media education of the 21st century. Chicago, IL: The MacArthur Foundation.

Mayhew, M.J., Wolniak, G.C., & Pascarella, E.T. (2008). How educational practices affect the development of life-long learning orientations in traditionally-aged undergraduate students. Research in Higher Education. 49(4), 337-356.

 

Von Stumm, S., Hell, B., & Chamorro-Premuzic, T. (2011). The hungry mind: Intellectual curiosity is the third pillar of academic. Perspectives on Psychological Science, 6(6), 574-588.

Tomorrow's Professor: Is Intellectual Curiosity a Strong Predictor for Academic Performance?

FREE Webinar: Converge Special Report Webinar Update: Specialty Classroom Technologies

Converge Special Report Update: Specialty Classroom Technologies A whole new class of specialized learning tools and technologies are appearing in classrooms today and are expected to increase in the near future. This influx of new classroom technology is driven by Common Core and other curriculum standards, student demand for cutting-edge technology and the need to produce a more globally competitive workforce. Specialty classroom technologies are also being used in the area of workforce readiness. Campuses face challenges both in trying to interest students in certain fields that are hiring as well as to retain them through graduation. However, a whole new class of specialized technology is emerging that not only can make up for campus’ limited resources, but can spark student engagement. To equip students with the skills they need, K-12 and Higher Education institutions are now employing intensive and often specialized technologies such as: Math and science labs Gaming, animation and media programming labs Art labs GIS/CAD labs Project-based learning environments Virtual models and simulation games Special needs programs This webinar will discuss how these technologies and others are being implemented to deliver near real-world experiences to students in schools around the country. Please join us! Complimentary Webinar Thursday, January 17, 2013 11:00 am PT/2:00 pm ET Duration: 1 hour Moderator Tom Ryan, Ph.D. Sr. Fellow, Center for Digital Education Former CIO, Albuquerque Public Schools Speaker Moses A. Ojeda Principal (I.A.) Thomas A. Edison Career & Technical Education High School, NY For questions or more information, please contact: Michael Shane Registration Coordinator 800-940-6039 ext. 1410 mshane@centerdigitaled.com Sponsored by:

 

© e.Republic. All rights reserved. 100 Blue Ravine Road, Folsom, CA 95630. Phone: 916-932-1300

FREE Webinar: Converge Special Report Webinar Update: Specialty Classroom Technologies

Dillard University SPRING 2013 IEA SCHEDULE OF ACTIVITIES

SPRING 2013 IEA SCHEDULE OF ACTIVITIES Location: DUICEF 207 (Unless noted otherwise)
DAY	DATE	ACTIVITY	NOTES
Wednesday	January 9	QEP Workshop	QEP Faculty Only
Tuesday	January 15	Presentation: Fall 2012 Student Evaluation of Faculty Results & FAQs	All Teaching Faculty
Friday	January 18	2012 NSSE Results Workshop: Faculty	1:00pm – 2:00pm
Friday	January 18	2012 NSSE Results Workshop: Staff	2:30pm – 3:30pm
Tuesday	January 22	IE Workshops: Completing Your IE Fall 2012 (and prior) Reports	Academic and administrative units are asked to sign-up for 2 hour slots (9a – 10:50a, 2p – 3:50p)
Friday	January 25	IE Workshops: Completing Your IE Fall 2012 (and prior) Reports	Academic and administrative units are asked to sign-up for 2 hour slots (9a – 10:50a, 11a – 12:50p, 2p – 3:50p)
Wednesday	January 30	WEBINAR: Deepening Learning Through E-Portfolios	All Teaching Faculty
Wednesday	February 27	Administer NSSE in Senior Courses	All Day in Computer Labs
Tuesday and Thursday	February 26 & 28	Administer CLA to Selected Seniors	All Day in Computer Labs
Monday – Friday	March 4 – 8	Administer NSSE in Freshman Courses	All Day in Computer Labs
Tuesday	March 19	IE Workshop:  Developing Measurable Outcomes for Administrative Units	Administrative units are asked to sign-up for 2 hour slots (9a – 10:50a, 11a – 12:50p, 2p – 3:50p)
Wednesday	March 20	IE Workshop:  Developing Measurable Outcomes for Administrative Units	Administrative units are asked to sign-up for 2 hour slots (9a – 10:50a, 11a – 12:50p, 2p – 3:50p)
Monday – Friday	March 25 – 29	Administer Survey of Faculty Advisors	Expect more details soon.
Monday – Friday	April 8 – 12	Administer Student Evaluation of Faculty	Interested faculty will be invited to sign up for labs
Tuesday – Wednesday	May 14 – 15	IE Workshops: Completing Your Spring 2013 IE Report	Academic and administrative units are asked to sign-up for 2 hour slots (9a – 10:50a, 11a – 12:50p, 2p – 3:50p)

 

Dr. Carla L. Morelon

Director of Institutional Effectiveness and Assessment

Office: Rosenwald 301

Phone: 504.816.4165

cmorelon@dillard.edu

Dillard University SPRING 2013 IEA SCHEDULE OF ACTIVITIES