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Taking Different Paths: A Comparative Study of Mentoring Models Among Robotics Competition Teams

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2013 ASEE Annual Conference & Exposition


Atlanta, Georgia

Publication Date

June 23, 2013

Start Date

June 23, 2013

End Date

June 26, 2013



Conference Session

Issues in Advising and Mentoring

Tagged Division

Educational Research and Methods

Page Count


Page Numbers

23.1130.1 - 23.1130.13



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Paper Authors


Nathan Dolenc University of Virginia

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1st Author
Nathan Dolenc
Ph.D. Student
Science Education
University of Virginia

2nd Author
Robert H. Tai
Associate Professor
University of Virginia

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Taking Different Paths: A Comparative Study of Mentoring Models Among Robotics Competition Teams Mentoring is believed to lead to high levels of success in both personal and professionalendeavors (Merriam, 1983). Mentors play a large role in out of school robotics programs wheremany have begun viewing robotics as a new approach to improving education and interest inscience, technology, engineering, and mathematics (STEM) (Barker et al, 2007). Studentsinvolved in robotics activities and competitions show an increase in attitude toward science(Welch, 2009) and possess a greater awareness of engineering careers (McGrath et al, 2009). Objective This study investigates the role of mentors in twelve different robotics teams involved inthe FIRST Robotics Competition (FRC), a high school robotics contest focused on inspiringstudents to enter STEM careers. Mentorship visions and involvement within these robotics teamsare compared to establish end points, and characterized to find where the remainder mentorvisions fall within this spectrum. Our research questions are: How do mentorship visions andlevels of involvement from different robotics teams compare with one another? What arethe various student behaviors under these mentorship visions? Methods Twelve robotics teams were observed and sixty-five interviews of mentors and studentswere conducted during the official FRC build and competition seasons. Observations focused onmentors’ and students’ behavior, actions, and comments during meetings and at competitionevents. Close observations were conducted as the author was allowed to move freely withinworkspaces, sit in on meetings, listen to small discussions, and watch during game play as longas the author did not impede each team’s progress. A grounded theory approach (Strauss &Corbin, 1998) was used for data analysis. The emerging themes from the data formed five areas:levels of involvement, types of learning, views of pathway, views of success, and behavioraloutcomes. Levels of involvement describes the amount of decision making occurring within thementor-student relationships. Types of learning describes the methods used for students toacquire new knowledge. Views of pathway describes how mentors and students interpret theirtime spent preparing their robot for competition. Views of success describes how mentors andstudents evaluate themselves and their team. Behavioral outcomes describes behavioral patternsobserved under the contrasting mentor visions. Findings Mentors possess a vision of how their robotics team should be organized. The keyingredient to each mentor’s vision is the amount of involvement and decision-making mentorstake part in. Two of the twelve teams were positioned at opposite ends of a mentorshipinvolvement spectrum. We defined the end of the spectrum with heavy mentorship involvementas the apprentice model where mentors make most of the decisions of design, construction, andstrategy in game play. We defined the other end of the spectrum with little to no mentorshipinvolvement as the autonomous model where mentors allow students to make the majority of thedecisions. The other ten teams and their mentors’ visions were compared within this spectrumand placed accordingly. This mentor-student behavior model can be used as a framework fortraining mentors and to analyze other out of school robotics competition teams. ReferencesBarker, S. B., Ansorge, J. (2007). Robotics as Means to Increase Achievement Scores in an Informal Learning Environment. Journal of Research on Technology in Education, 39(3), 229-243.Bozionelos, N. (2004). Mentoring provided: Relation to mentor’s career success, personality, and mentoring received. Journal of Vocational Behavior, 64(1), 24-46.Brandeis University (2005). More Than Robots: Evaluation of the FIRST Robotics Competition Participant and Institutional Impacts. Waltham, MA: Melchior, A., Cohen, F., Cutter, T., & Leavitt, T.Eby, L. T., Allen, T. D. (2002). Further investigation of protégés’ negative mentoring experiences: Patterns and outcomes. Group & Organization Management, 27(4), 456-479.FIRST Mentoring Guide (2007). Retrieved from, K. E., & Isabella, L. A. (1985). Mentoring alternatives: The role of peer relationships in career development. Academy of Management Journal, 28(1), 110-132.Merriam, S. (1983). Mentors and Protégés: A Critical Review of the Literature. Adult Education Quarterly, 33(3), 161-173.McGrath, E., Lowes, S., Lin, P., & Sayres, J. (2009). Analysis of Middle-and High School Students’ Learning of Science, Mathematics, and Engineering Concepts Through a LEGO Underwater Robotics Design Challenge. American Society for Engineering Education Annual Conference, Austin, TX, June 2009.National Academies (2005). Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Economic Future. Washington, D.C.: National Academies Press.Strauss, A., Corbin, J. (1998) Basics of Qualitative Research. Grounded Theory Procedures and Techniques 2nd Ed. Newbury Park, CA: Sage.Welch, A. G. (2009). Using the TOSRA to Assess High School Students’ Attitudes Toward Science After Competing In the FIRST Robotics Competition: An Exploratory Study. Eurasia Journal of Mathematics, Science & Technology Education, 6(3), 187-197.

Dolenc, N. (2013, June), Taking Different Paths: A Comparative Study of Mentoring Models Among Robotics Competition Teams Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--22515

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