Date of Award

Fall 2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

STEM and Professional Studies

Committee Director

Jill E. Stefaniak

Committee Member

Tian Luo

Committee Member

Angela Eckhoff

Abstract

This study extends the literature on academic help-seeking by identifying factors influencing undergraduate students’ selection of a source of help. Learners engage in intentional decisions to seek help from human and non-human sources to resolve gaps in knowledge. Decision making heuristics provide a theoretical lens to understand these intentional decisions. Previous research in academic help-seeking assumed learners sought only human sources of assistance, resulting in a narrow understanding of how learners resolve knowledge gaps. Methodological trends in help-seeking research consistently favor quantitative, survey based tools with pre-defined options. As a result, the factors that influence the selection of a source in a real world setting with both human and online sources remains unexplored.

This mixed methods study documented actual help-seeking behavior. Participants recorded source utilization during an in-class problem solving activity and documented out-of-class activity through a survey. The survey also captured participant’s perceptions of a newly proposed help source classification matrix as well as a recently proposed expectancy value model of source selection. A self-selected sample (n = 25) of the participants completed semi-structured follow up interviews.

Grounded theory methodology guided the qualitative phase. The results demonstrate that undergraduate students utilize online and human sources with similar intentions and confirm factors unidentified by previous research influence the source selection process. These factors include an expectation of reciprocity, relevance, domain, time, type of assignment, availability of sources and an expanded understanding of the role of faculty. The findings also demonstrate evidence of decision making heuristics.

The findings of this study support and expand on important recent work suggesting the inclusion of online sources in help-seeking models and the importance of relationships as well as underscore the need for the development of an integrated framework for understanding help-seeking in a realistic setting. Information seeking may serve as an appropriate theoretical framework to integrate academic help-seeking and information-searching behavior. The study suggests that the proposed expectancy value matrix and classification matrix may not prove robust enough to integrate human and non-human source usage behavior. This study demonstrates the value of qualitative approaches towards understanding academic help-seeking behavior.

ISBN

9781369564204

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