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Irina Tyshkevich

Agents for change: Robotics for girls: A robotics curriculum for middle school years & The Impact of Robot Projects on Girls’ Attitudes Toward Science and Engineering . Irina Tyshkevich. By: Leonne Tanis Advisor: Dr. Jim Ostrowski, Professor of Mechanical Engineering.

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Irina Tyshkevich

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  1. Agents for change: Robotics for girls: A robotics curriculum for middle school years&The Impact of Robot Projects on Girls’ Attitudes Toward Science and Engineering Irina Tyshkevich

  2. By: Leonne Tanis Advisor: Dr. Jim Ostrowski, Professor of Mechanical Engineering EAS99: A Review of the Agents for Change Program: Robotics for Girls Project Summer 2000 - Summer 2001 • Agents for Change: Robotics for Girls Project is a four-year project that hopes to correct under representation of girls and women in science and technology. • The project uses robotics to elicit interest among girls, teaching them about how robots function and circuits. • The project also hopes to make science and math fun, because they are often viewed as boring and scare girls away • Lego Mindstorm combines Lego fun and computer programming software called LOGO, allowing children to both build and program the robots • The main robot they worked on gearing up was the GearBot and given a deeper introduction to robots in the GRASP lab • The project was a series of summer camps which then turned into after school clubs • The author observes that the program has really helped girls. At first they start off apprehensive, but later start actively participating as their confidence increases. By: Leonne Tanis Advisor: Dr. Jim Ostrowski, Professor of Mechanical Engineering

  3. The Impact of Robot Projects on Girls’ Attitudes Toward Science and Engineering We’ve heard a lot about how STEM education attracts the interest of younger students and especially girls to the fields of science, technology, engineering and mathematics, but does the interest actually influence them to continue on to an Engineering career? This paper researches exactly this question of long term career interest. • Robots and robotics projects are affordable engaging educational tools that have been adopted by many programs • This study takes into account various cultural and education aspects of the girls’ experience with STEM in order to see if STEM concepts translate into long term interests • To examine the social and cultural issues, the study applied Wigfield and Eccles’s expectancy-value theory which argues that individuals’ choice are directly related to their “belief about how well they will do on an activity and the extent to which they value the activity” • The study shows that many factors are involved in a student’s experience in a robotics education program and they all contribute to self-perception of success – the study focused on children’s perceptions, goals, abilities, and expectations of success By Jerry B. Weinberg, Jonathan C. Pettibone, Susan L. Thomas, Mary L. Stephen, and Cathryne Stein

  4. Psychological Components • Gender make-up of the STEM teams • The girls’ perceptions of gender roles in STEM activities • The girls’ long term goals in STEM • The girls’ self-perceived abilities in STEM areas • The girls’ expectations of success in STEM areas • STEM related short term and long term academic career choices

  5. Method: KISS Institute for Practical Robotics’ Botball Program – a regional and national robotics competition in a team-based activity. Participants were tested pre and post the program. “The quantitative study was complemented by a qualitative study that followed four teams: two all-girl teams and two mixed-gender teams. The qualitative study helped us to identify and understand “causal connections in the lived experiences of participants” [18, p. 15]. It also allowed us to gain an understanding of girls’ unique and personal experiences and what effects participation may have on their future decisions. Data were collected from several sources, including interviews of parents, mentors and students; observation of team sessions; videotapes by both researchers and student participants of team sessions; and documentation and blog entries produced by the team members. Data from the different sources provided a multi-layered understanding of participants’ experiences that enabled us to create thick, descriptive narratives of each team. Trustworthiness of research findings was established through triangulation of data. Triangulation involves cross-checking interpretations and data obtained from multiple, independent approaches and sources [18].”

  6. Experimental Results Quantitative Data – 1). (SEM) Structural Equation Modeling: a technique that allows for the modeling of relations between multiple variables, in particular perceptions, goals and self-schemata and how they affect achievement related choices. They found that beliefs in traditional gender roles led to negative self-concepts of ability which in turn led to lower expectations for success in science and math. And vice versa2). They used the result of the model to look for the impact of participation in BotBall. Using Analysis of Varainces (ANOVA’s), they found that the attitudes of girls towards a career in engineering significantly increased as a result of participation. This worked best in mixed gender teams Qualitative Study – Mentors were extremely important and greatly affected the way that the girls viewed themselves

  7. Conclusion “The results of this study provide evidence that participation in Botball may help to reduce the gender gap in science and engineering through reducing beliefs in traditional gender roles and increasing positive attitudes about engineering and science and careers in these areas. Given that the Botball program lasts only seven weeks, these results indicate that short-term, well-structured programs that can effectively modify social and cultural beliefs may be particularly promising in encouraging girls to pursue STEM areas for study and careers.”

  8. Review • Definitely a current and significant topic • Some generalizations, but a good approach • Very relevant issue and related to robotics • Slightly underdeveloped • Good data, but more would be nice

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