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Record W2615656561 · doi:10.7939/r33j39b71

Exploring Undergraduate Perceptions of Meaning Making and Social Media in their Learning

2016· dissertation· en· W2615656561 on OpenAlexaboutno aff
Erika E. Smith

Bibliographic record

VenueMount Royal University Institutional Repository (Mount Royal University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)Social mediaPerceptionMeaning-makingPsychologyPedagogySociologyMathematics educationComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Those concerned with teaching and learning in higher education and the Net generation’s perspectives on and uses of technology must address calls to move beyond the digital native debate (Bennett & Maton, 2010; Kennedy, Judd, Dalgarno, & Waycott, 2010) by asking students directly what they see as a meaningful part of their learning. This study aims to move beyond the digital native debate by developing research-informed understandings of the ways in which Net generation students may perceive technologies, specifically social media, to be a meaningful part of their undergraduate learning. The research questions guiding this study include: (RQ1) In what ways do undergraduate learners from different disciplines view social media to be a meaningful part of their university learning? (RQ2) What characteristics of social media do undergraduate learners see as contributing to their meaning making during their university learning? This study uses a social constructivist approach, thereby employing two main premises: learners actively construct their own knowledge, and social interactions are an important part of knowledge construction (Woolfolk, Winne, Perry, & Shapka, 2010, pp. 343-344). The research design is a mixed methods research (MMR) methodology, a methodological approach where a combination of methods is intentionally used to best address the research questions (Creswell, 2008; Creswell, 2015). This study’s MMR design involved a first phase qualitative component of intensive, semi-structured interviews with 30 undergraduate students enrolled in full-time studies at the University of Alberta, a large, Canadian, research-intensive university – with ten students from each of the three disciplinary areas of 1) humanities and social sciences, 2) health sciences, and 3) natural sciences and engineering, analyzed using a generic qualitative approach (Merriam, 2009) incorporating constructivist grounded theory techniques (Charmaz, 2014). The second phase quantitative component was comprised of undergraduate students across disciplines with survey responses (N = 679) regarding their perspectives on and uses of social media technology in their university learning. This phase included two pilot surveys conducted before the final survey was distributed to ensure the reliability and validity of the instrument developed. Survey responses were collected electronically via SurveyMonkey, and analyzed via descriptive statistics. The findings in this study shed new insights into student perspectives and uses of social media, and the variety of ways in which undergraduates intentionally chose (or, chose not) to incorporate social media into their university learning in meaningful ways. The interviews provide a detailed picture of undergraduate perspectives regarding the specific ways in which social media can help and hinder learning, comprising what students consider as a double-edged sword. Student perspectives and descriptions formed key recurring themes, which emerged into several core characteristics of social media, as well as core categories of meaning making in undergraduate university learning. Within the qualitative interviews and the open-ended survey results, there is an overarching theme of social media as a double-edged sword that both informs and distracts, having the potential to both help and hinder learning. Together, the qualitative and quantitative results demonstrate that several contextual relationships exist, including an important relationship between the particular ways of meaning making identified and the specific social media technologies undergraduates use for their university learning. For those concerned with social media in higher education, these results show how factors such as age and digital native claims should not be seen as primary, deterministic elements of technology use. Rather than taking an approach founded upon technological determinism, the idea of a generational zeitgeist should be considered, where learning context and social media affordances become key.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.236
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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Same venueMount Royal University Institutional Repository (Mount Royal University)Same topicImpact of Technology on AdolescentsFrench-language works237,207