Making Visible the Behaviors that Influence Learning Environment: A Qualitative Exploration of Computer Science Classrooms

Barker, Lecia; Garvin‐Doxas, Kathy

doi:10.1080/08993400412331363853

Cited by 76 publications

(60 citation statements)

References 25 publications

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“…More specifi cally, many STEM courses encourage competition for grades, which promotes an emphasis on individual success rather than on collaborative learning (Strenta and others, 1994;Astin andSax, 1996, Seymour andHewitt, 1997). Such an environment can be especially discouraging to women, who tend to prefer more cooperative forms of learning (Barker and Garvin-Doxas, 2004).…”

Section: Attracting and Retaining Women In Stemmentioning

confidence: 99%

Major selection and persistence for women in STEM

Shapiro

Sax

2011

New Drctns for Instit Rsrch

140

117

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Section: Attracting and Retaining Women In Stemmentioning

confidence: 99%

Major selection and persistence for women in STEM

Shapiro

Sax

2011

New Drctns for Instit Rsrch

140

117

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“…Factors related to persistence that have been studied (cf. [4][6] [7][10]) include the positive impact of prior experience with programming (shown to be positively associated with success in introductory courses) as well as pace and workload; a negative relationship between perceived low grades and persistence (with women leaving at higher rates than men, even with the same grades); a perception of low social relevance or meaningfulness of curricula and assignments; low levels of student-faculty interaction, including faculty attitudes, feedback, encouragement, mentoring, and career advice; problems associated with student-student interaction, such as not feeling like one belongs, a heavy focus on individualized learning, or lack of access to peer support networks; issues of pedagogy, such as the positive influence of collaborative learning on retention (e.g., pair programming); and the quality and training of teaching assistants. For students who are members of groups underrepresented in computing, a lack of role models has been hypothesized as problematic [7].…”

Section: Literature On Student Persistencementioning

confidence: 99%

“…Astin's Input-Environment-Output model [1] has influenced most conceptual frameworks for accounting for and planning programs for student outcomes in institutions of higher education (e.g., [2][3] [4][10] [12][15] [17] ). Factors related to student persistence generally include student background characteristics (e.g., gender, race/ethnicity, pre-college educational experiences); institutional characteristics (e.g., size, selectivity); student-faculty and student peer interaction; student satisfaction with the learning environment; and students' ability to be involved in the academic experience (both educational and social) [2] [12].…”

Section: Literature On Student Persistencementioning

confidence: 99%

Exploring factors that influence computer science introductory course students to persist in the major

2009

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This paper describes an exploratory study to identify which environmental and student factors best predict intention to persist in the computer science major. The findings can be used to make decisions about initiatives for increasing retention. Eight indices of student characteristics and perceptions were developed using the research-based Student Experience of the Major Survey: student-student interaction; student-faculty interaction; collaborative learning opportunities; pace/workload/prior experience with programming; teaching assistants; classroom climate/pedagogy; meaningful assignments; and racism/sexism. A linear regression revealed that student-student interaction was the most powerful predictor of students' intention to persist in the major beyond the introductory course. Other factors predicting intention to persist were pace/workload/prior experience and male gender. The findings suggest that computer science departments interested in increasing retention of students set structured expectations for student-student interaction in ways that integrate peer involvement as a mainstream activity rather than making it optional or extracurricular. They also suggest departments find ways to manage programming experience gaps in CS1.

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“…Despite the recent surge in enrollment in CS, women and minorities are still underrepresented: for example, in 2013, women earned only 13 % of bachelor's degrees in CS, African-Americans 3.8 % and Hispanics 6 % -African-Americans and Hispanics made up 15 % and 14 % of undergraduate students in the U.S., respectively (Zweben and Bizot 2015;Monge et al 2015). Among the many suggestions from researchers who explore possible reasons for low participation by females (Fisher et al 1997;Gürer and Camp 2002;Wilson 2002, Katz et al 2003Barker and Garvin-Doxas 2004) is the behaviors of students and instructors in CS classrooms. Barker and Garvin-Doxas (2004) explored the discourse in multiple CS classrooms and found communication patterns that were indicative of "an impersonal environment with guarded behavior" and of participants creating and maintaining a hierarchy based on programming experience that resulted in competitive behaviors.…”

Section: Attrition and Underrepresentation In Computer Science Educationmentioning

confidence: 97%

Shifting the Load: a Peer Dialogue Agent that Encourages its Human Collaborator to Contribute More to Problem Solving

Howard

Jordan

Eugenio

et al. 2015

Int J Artif Intell Educ

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Despite a growing need for educational tools that support students at the earliest phases of undergraduate Computer Science (CS) curricula, relatively few such tools exist-the majority being Intelligent Tutoring Systems. Since peer interactions more readily give rise to challenges and negotiations, another way in which students can become more interactive during problem solving, we created an artificial peer collaborator to determine its value for aiding CS students. Central to its development was the notion that it should monitor the student's collaborative behavior and attempt to guide him/her towards more productive behavior. In prior work, we found that initiative shifts correlate with both Knowledge Co-Construction (KCC) and learning and are potentially easier to model as an indicator of productive collaboration in instructional software. In this paper, we describe a unique peer dialogue agent that we created to test the effects of tracking and reacting to initiative shifts. & Engineering Offices (MC 152) 851 South Morgan, Chicago, IL 60607, USA Int J Artif Intell Educ While our study did not find differences in learning gains when comparing agents that do and do not track and react to initiative shifts, we did find that students do learn when interacting with the agent and that attempting to influence initiative taking did make a difference. This suggests that by tracking initiative shifts, the agent was able to detect times when the student had been letting the agent do most of the "deep thinking" and that the agent's tactics for encouraging the student to begin taking the initiative again were helpful.

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Making Visible the Behaviors that Influence Learning Environment: A Qualitative Exploration of Computer Science Classrooms

Cited by 76 publications

References 25 publications

Major selection and persistence for women in STEM

Major selection and persistence for women in STEM

Exploring factors that influence computer science introductory course students to persist in the major

Shifting the Load: a Peer Dialogue Agent that Encourages its Human Collaborator to Contribute More to Problem Solving

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