1 / 60

Boosting Scientific Literacy and Interest Among Underprivileged Middle School Students Using Experiential Learning Theor

InnoWorks. Boosting Scientific Literacy and Interest Among Underprivileged Middle School Students Using Experiential Learning Theory And College Volunteers. Vineet Agrawal, Ahrash N. Bissell, William L. Hwang, Daniel M. Kaplan, Jessica E. Manson, Matthew K. Mian.

vinny
Télécharger la présentation

Boosting Scientific Literacy and Interest Among Underprivileged Middle School Students Using Experiential Learning Theor

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. InnoWorks Boosting Scientific Literacy and Interest Among Underprivileged Middle School Students Using Experiential Learning Theory And College Volunteers Vineet Agrawal, Ahrash N. Bissell, William L. Hwang, Daniel M. Kaplan, Jessica E. Manson, Matthew K. Mian 2006 Scholarship of Teaching & Learning Faire Western Carolina University February 23, 2006

  2. Overview • What is InnoWorks? • Motivation and rationale • Goals • Program development and structure • Evaluating InnoWorks • Student interest in science and learning gains • Mentor training and gains • LSI and ELT as guide for program structure and mentor strategies • Future Outlook

  3. Mission Statement Design and implement innovative workshops and programs in science and engineering for students from underprivileged backgrounds.

  4. What is InnoWorks? • Student-founded and led 501(c)(3) non-profit educational organization • Completed two successful years and exciting outlook for future • Current chapters: Duke, UMCP • 2006 chapters: Georgetown, UPenn • Global interest: England, Saudi Arabia, India

  5. Goals • Establish links between classroom science and engineering and the real world through fun, engaging activities • Encourage students to consider science and engineering as potential career paths • Foster teamwork and development of strong work ethic • Provide positive role models and develop lasting relationships

  6. Target group • Middle school students (11-14 yrs) • Enough maturity, yet still impressionable • Students from underprivileged backgrounds • Unable to afford science camps, and may grow up in environments that lack academic role models

  7. Student Nominations • Recommendations by principals, counselors, teachers, and community leaders • Student interest in science/engineering but lack of opportunities

  8. CBS (WRAL 5)

  9. US is falling behind in STEM education Low high school graduation rates—particularly for minorities “Achievement gap” shown to widen with age Motivation

  10. Mentoring shown to be effective for inspiring students to succeed in and out of the classroom Increasing and helping to sustain enthusiasm for science Contributing research and data to broader educational community Offering a model for supplemental-education and service-learning programs Potential Impact

  11. Free week-long program (includes food, transportation, prizes, t-shirts, etc.) Morning presentation followed by hands-on activities and competitive missions Students work in teams of 3-4, each mentored by 1-2 college students Program Structure

  12. Missions involve design and experimentation to solve real-world problems Students formally present their solutions Teams rewarded for teamwork and success in missions Curriculum designed to be flexible and modular Structure Cont’d

  13. College students with a passion for sharing interests & knowledge Age and experience make them ideal role models Offers college students a meaningful role in community outreach Students as Mentors

  14. D. A. Kolb’s “experiential learning cycle” Four essential learning processes: concrete experience, reflective observation, abstract conceptualization, and active experimentation J. Zull: learning cycle reflected in physical structure of brain Our goal: Engage all stages of the learning cycle Program activities are designed from the ground up with these educational principles in mind Reflective questions after each mission => metacognition A Novel Approach To Mentoring & Learning

  15. 44 participants at Duke, 32 at UMD InnoWorks 2005: Making Sense of Senses

  16. Theme: Human senses Curriculum, mentoring methods, research, and program logistics published in two books InnoWorks 2005: Making Sense of Senses …and the future: InnoWorks 2006 entitled “Explorations” – students will explore the oceans, outer space, the rainforest, and more!

  17. Duke News & Communication

  18. Program Outcomes • Was the InnoWorks program successful? • Our data suggest that InnoWorks was an enormous success • Student responses • Mentor responses • Family responses • Community responses • Sponsor responses

  19. Program Evaluation • Many different approaches to evaluating and improving program • We are sharing student and mentor gains as overall assessments of the program • We also selected one particular area of research we incorporated into the program this past year, related to learning styles

  20. Student Gains • Pre- and post- surveys were electronically administered on the first and last days of the camp, respectively • Data collected and compiled were based on responses of 60 students (31 females, 29 males) • Students were asked to be completely honest, and they were assured there would be no repercussions for negative responses

  21. Student Demographics • 80% of the students were middle school students

  22. Student Pre-Survey “How interested are you in science?”

  23. Student Pre-Survey “How important will science be in your future?” • 24 students indicated interest in a scientific career

  24. Student Pre-Survey “How hard do you try in school?”

  25. Student Feedback • 55/60 students stated they understood science better as a result of InnoWorks • 51/60 students stated they were more interested in learning science after InnoWorks • 90% would recommend InnoWorks to a friend • Over 94% of the students would participate in InnoWorks again • Of the 22 that reported “Very Interested” in science, all but one were even more interested in learning science afterwards

  26. Student Feedback • 52/60 students feel better about being able to learn science as a result of InnoWorks • 51/60 students stated they learned some things in this program that they can use in a science class in school in the future • 50/60 students were now more aware of the importance of science in everyday life as a result of InnoWorks • 54/60 students told their family/friends what they did in the program

  27. Student Reflections

  28. Staff-Student Composition • Duke • 12 mentors • 18 staff • 44 students • Maryland • 14 mentors • 20 staff • 32 students

  29. Number of Mentors Matters • Mentors preferred the two-mentor model • Division of labor • Disciplinarian • Teacher • Closer guidance • Idleness a potential drawback

  30. Quotations “. . . by having Duke students as mentors, the students received the information in a much more relaxed setting among people they could consider as role models, peers, and friends.” – Jessica Manson (Duke)

  31. Quotations “Almost as a rule for these three students, the more that they could see practical applications to an activity or mission, the more they enjoyed it.” – Amit Patel (Duke and Maryland)

  32. Quotations “It’s really heartwarming to see kids respond to the program and I feel that that’s why we exist. Overall, mentoring was a great experience and one that I would recommend to others.” – Bilal Aijazi (Maryland)

  33. Exit Survey Results(for mentors) • The structure of InnoWorks helped to keep students motivated and excited • Their leadership skills and their abilities to comprehend and apply science-related knowledge improved • Room for improvement in mentor training; many felt under-prepared for their duties

  34. Learning-Styles Theory • Recent advances in brain sciences are informing our understanding of how people learn • Synthesis of neurobiology, cognitive science, and educational theory: Dr. James Zull of Case Western Reserve University • Interesting parallels between one of the most widely used and tested learning-styles inventories (Kolb’s LSI) and the physical and functional structure of the brain

  35. Learning-Styles Theory • Four stages of Kolb’s learning cycle • Concrete Experience • Reflective Observation • Abstract Conceptualization • Active Experimentation

  36. Active Testing CONVERGER ACCOMODATOR Motor Cortex Sensory Cortex Concrete Experience Abstract Hypotheses Frontal Integrative Cortex Back Integrative Cortex ASSIMILATOR DIVERGER Reflective Observation Learning-Styles Theory

  37. Impact on InnoWorks • InnoWorks is designed to try and exploit every stage in the learning cycle • Provides a different way of thinking about the value of certain program elements than most programs of this type • Emphasis is not simply on doing cool, attention-grabbing things • While “cool” factor was definitely there, intent was to provide concrete experiences from which to engage students in rest of the cycle

  38. Kolb’s LSI • Administered LSI on first and last days of program • In theory, we can measure whether students evolved in terms of their learning preferences by measuring shifts in LSI scores • Since InnoWorks is intended to encourage all stages of learning, we would not necessarily predict a shift in any particular direction • We are only presenting a partial analysis here

  39. Kolb’s LSI • Four calculated scores • MATLAB script to compute and produce “kite plot”

  40. Converger Shift • 33 of 60 students exhibited a change in preferred learning style • Converger category transitioned from having fewest (9) to most (19) students, whereas all other categories had decreases

  41. Converger Shift • Possible interpretations of “converger shift” • Science and engineering in general tend to emphasize converging stage; perhaps any enjoyable science learning experience disposes participants toward preferring this quadrant? • Perhaps program didn’t emphasize all stages of learning cycle equally? The converging stage may have been emphasized more, so students, through their enjoyment the camp, now feel they prefer that stage of the cycle?

  42. Converger Shift • Possible interpretations of “converger shift” • Perhaps the students were particularly encouraged to use converging stage by mentors? Most mentors and curriculum developers were convergers.

  43. Student Effort & LSI Shifts • Average self-reported effort made by students to understand science at InnoWorks • 4.63/5.00 for shift in learning preference • 4.31/5.00 for no shift in learning preference • Paired T-test, p = 0.070 • Result suggests that changes in LSI scores may reflect engagement with InnoWorks program, as opposed to random changes over time or better understanding of survey

  44. LSI Research Questions • Does the LSI have predictive value in the InnoWorks setting? • Does the preferred learning styles of mentors and students have any correlation with mentor effectiveness? • Are group dynamics correlated with team learning style composition?

  45. Predictive Value • All mentors that addressed this question found that there was significant correlation between student behaviors and the LSI results for most students “For each of the members of our team, it was striking how well the pre-camp LSI agreed with our first impressions, and to some extent the changes between the first and second LSI measurements were also in accordance with our observations throughout the weeks.” (Lisa Richards, Duke)

  46. Clarifying Learning Styles • For students that changed their learning style, mentors often found that results of second LSI were more accurate • Some changes in LSI were not so much the result of actual changes in learning style but in the students’ understanding of how they like to learn • Most students could roughly evaluate their own learning preferences

  47. Impact of Mentor LS • Most mentors found it much easier to mentor students with similar learning styles to themselves • Teams that had two mentors: each mentor found that they were most compatible with students in their group with similar learning styles “The way a mentor learns could affect the interaction between mentor and student. For example, I am an assimilator. I tend to work better with Ashley and Amanda, whose kite is more similar to mine than that of the other two. However, Sharad is a converger/accommodator. He was much more capable at getting Cydney and Kenneth interested in the projects than I was. However, he did not connect with Amanda or Ashley.” (Nita Amornsiripanitch, Duke)

  48. Impact of Mentor LS • One mentor with perfectly symmetrical LSI kite plot could relate to and motivate all students easily • Numerous other factors that play a role in mentor-student interactions (e.g., background, gender, personality)

  49. Group Dynamics • Little agreement between mentors on if and how learning styles of students had an effect on group dynamics • Similar learning styles: team members could relate better, help each other, same difficulties • Different learning styles: better distribution of tasks • Some groups had clear cooperative grouping based on learning styles

  50. Future LSI Research • Ultimate goal: knowledge and methods from cognitive neuroscience can lead to effective techniques of providing insight into how to help a student learn most effectively • Well-trained mentors can strengthen learning abilities and confidence of students by using latter’s learning strengths to address their learning weaknesses

More Related