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Analysis of the Implementation of the How People Learn Framework Through Direct Classroom Observation in Selected Food Engineering Courses

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Collection

2011 ASEE Annual Conference & Exposition

Location

Vancouver, BC

Publication Date

June 26, 2011

Start Date

June 26, 2011

End Date

June 29, 2011

ISSN

2153-5965

Conference Session

Biological & Agricultural Poster Session

Tagged Division

Biological & Agricultural

Page Count

17

Page Numbers

22.207.1 - 22.207.17

Permanent URL

https://peer.asee.org/17488

Download Count

17

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Paper Authors

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lourdes gazca American University, Puebla, Mexico

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Lourdes Gazca is Science, Engineering, and Technology Education Ph.D. Student at Universidad de las Americas Puebla in Mexico. She teaches mathematics and statistics related courses. Her research interests include faculty development, active and cooperative learning, and creating effective learning environments.

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Aurelio Lopez-Malo American University, Puebla, Mexico

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Enrique Palou American University, Puebla, Mexico

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Enrique Palou is Director, Center for Science, Engineering, and Technology Education; and Professor, Department of Chemical, Food, and Environmental Engineering at Universidad de las Americas Puebla in Mexico. He teaches engineering design, food science, and education related courses. His research interests include emerging technologies for food processing, creating effective learning environments, and building rigorous research capacity in science, engineering and technology education.

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Abstract

Analysis of the Implementation of the How People Learn Framework Through Direct Classroom Observation in Selected Food Engineering CoursesThe How People Learn (HPL) framework [1, 2] was used to redesign two food engineeringcourses, Introduction to Engineering Design (EI-100) and Food Chemistry (IA-332), to furtherpromote an interactive classroom while integrating multiple formative assessments by means ofTablet PC technologies [3]. The HPL framework highlights a set of four overlapping lenses thatcan be used to analyze any learning situation. In particular, it suggests that we ask about thedegree to which learning environments are knowledge, learner, community, and assessmentcentered [1-3]. The VaNTH Observation System (VOS) is an assessment tool developed tocapture qualitative and quantitative classroom observation data from teaching and learningexperiences of the bioengineering classroom. VOS is a four-part system that incorporates HPLframework elements and uses four recurring methods of collecting classroom data: recordingstudent-teacher interactions (CIO), recording student academic engagement (SEO), recordingnarrative notes of classroom events, and rating specific indicators of effective teaching [4, 5].VOS was used to systematically assess HPL framework implementation in EI-100 and IA-332redesigned classrooms as well as in two “traditional” courses, Material Balances (IQ-210) andBiophysics (FS-270). Observers measured differences in classroom experiences resulting fromthe innovations and redesigned learning environments as well as in IQ-210 and FS-270. Therewere two EI-100 sections, section 1 with 40 students and section 2 with 68 students, while IA-332, IQ-210 and FS-270 had 23, 21 and 24 students, respectively. Thus, using the CIO, a total of252 observations were performed in each of the EI-100 sections (504 in all) during the semesterat a rate of six observations per class and three classes per week for 14 weeks, while 138, 100and 70 CIO observations were performed in IA-332, IQ-210 and FS-270, respectively. In termsof SEO, there were more observations because of the number of students enrolled in the courses:3360 observations for section 1, and 5712 observations for section 2 of EI-100, while 3174,2100, and 1680 SEO observations were performed in IA-332, IQ-210 and FS-270, respectively.Observers achieved a 75 percent inter-rater reliability in using the VOS.EI-100 and IA-332 redesign significantly (p<0.05) increased student participation whileformative assessments and feedback were more common. Instructors in these redesigned coursesutilized the information gained through real-time formative assessment to tailor instruction andmeet student needs. Particularly important were opportunities to make students’ thinking visibleas well as opportunities for “what if” thinking. VOS captured important differences betweenredesigned and “traditional” classroom experiences. These differences may be used to measurelevels of “HPLness” of a lesson. Moreover VOS clearly captured differences among instructors’teaching styles. In addition, VOS generated detailed feedback that instructors may use to self-assess. Student final grades in redesigned courses were higher than those found in “traditional”courses. Further, less students failed the course and the percentage of students who stayed in thecourse until the end was higher in the redesigned courses.[1] J. D. Bransford, A. L. Brown, and R. R. Cocking. How People Learn. Brain, Mind, Experience and School. Expanded Edition. National Academy Press. Washington DC (2000).[2] J. D. Bransford, N. Vye, and H. Bateman. Creating High-Quality Learning Environments: Guidelines from Research on How People Learn. In: The Knowledge Economy and Postsecondary Education: Report of a Workshop. P. Albjerg Graham and N. G. Stacey (Eds.). National Academy Press. Washington DC (2002).[3] E. Palou, L. Gazca, A. López-Malo, and J. M. Garibay. High-Quality Learning Environments for Engineering Design: Using Tablet PCs and Guidelines from Research on How People Learn. In: From Lectures to Active Learning: Technology and the Scholarship of Teaching. HP/ISTE Reimagining the Classroom: Innovations in Teaching & Learning with Technology Book Series. M. Barnett, J. Vanides (Eds.) International Society for Technology and Education, Washington DC (in press).[4] L.  Gazca, E. Palou, A. López-Malo, and J. M. Garibay. Capturing Differences of Engineering Design Learning Environments by Means of VaNTH Observation System. Proceedings of the American Society for Engineering Educational Annual Conference and Exposition, Austin, TX (2009).[5] A. H. Harris and M. F. Cox. Developing an Observation System to Capture Instructional Differences in Engineering Classrooms. Journal of Engineering Education. 92(4): 329-336 (2003).

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