University of Hertfordshire

Validating a social media typology with machine learning and focus groups

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Validating a social media typology with machine learning and focus groups. / Saward, Guy; Jefferies, Amanda.

Proceedings of the 15th European Conference on E-Learning. ed. / Jarmila Novotna; Antonin Jancarik. Reading, UK : ACPI (Academic Conference Publishing International), 2016. p. 640-649.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Saward, G & Jefferies, A 2016, Validating a social media typology with machine learning and focus groups. in J Novotna & A Jancarik (eds), Proceedings of the 15th European Conference on E-Learning. ACPI (Academic Conference Publishing International), Reading, UK, pp. 640-649, ECEL 2016, Prague, Czech Republic, 27/10/16.

APA

Saward, G., & Jefferies, A. (2016). Validating a social media typology with machine learning and focus groups. In J. Novotna, & A. Jancarik (Eds.), Proceedings of the 15th European Conference on E-Learning (pp. 640-649). ACPI (Academic Conference Publishing International).

Vancouver

Saward G, Jefferies A. Validating a social media typology with machine learning and focus groups. In Novotna J, Jancarik A, editors, Proceedings of the 15th European Conference on E-Learning. Reading, UK: ACPI (Academic Conference Publishing International). 2016. p. 640-649

Author

Saward, Guy ; Jefferies, Amanda. / Validating a social media typology with machine learning and focus groups. Proceedings of the 15th European Conference on E-Learning. editor / Jarmila Novotna ; Antonin Jancarik. Reading, UK : ACPI (Academic Conference Publishing International), 2016. pp. 640-649

Bibtex

@inproceedings{92c7170b8cff4222a96d9b749917692a,
title = "Validating a social media typology with machine learning and focus groups",
abstract = "Social media networks (SMN) are an established part of the learning landscape in which our students reside as digital inhabitants. Our work is built around an ongoing four-year survey of student attitudes and engagement with SMN and their educational use. Our pre-conceptions were that students would be less keen on engaging with staff via social media. However, the survey results showed only 14% of students against this. Using machine learning to investigate whether those for academic SMN use (dubbed “integrationists”) could be separated from those against (“separatists”) showed it was hard to predict students{\textquoteright} attitudes purely based on their patterns of use of SMN.The complexity of the issues is reflected by focus group work that identified SMN as just one part of a complex pattern of personal communication. For some, Facebook (FB) consumed more time compared to text/email, but the latter were seen as more privileged with use restricted to higher value conversations and participants. Other insights included conflicted views on the value of SMN, a functional view of SMN alerts, and the lack of immersion in academic SMNs. These results suggest SMN are not a panacea for student engagement. Care must be taken in designing effective learning conversations using appropriate media and interaction. Slavishly adopting social practices from SMN will not automatically benefit learners and may leave them more disengaged and distracted than ever",
keywords = "social media networks , student engagement, academic engagement",
author = "Guy Saward and Amanda Jefferies",
note = "This document is the Accepted Manuscript of the following paper: Guy Saward and Amanda Jefferies, {\textquoteleft}Validating a social media typology with machine learning and focus groups{\textquoteright}, in Proceedings of the 15th European Conference on E-Learning. Prague, Czech Republic 27-28 October 2016. Jarmila Novotna and Antonin Jancarik eds., ISBN 978-1-911218-18-0, e-ISBN 978-1-911218-17-3. Published by Academic Conference Publishing International (ACPI). ; ECEL 2016 : 15th European Conference on e-Learning ; Conference date: 27-10-2016 Through 28-10-2016",
year = "2016",
month = oct,
day = "26",
language = "English",
isbn = "978-1-911218-18-0",
pages = "640--649",
editor = "Jarmila Novotna and Antonin Jancarik",
booktitle = "Proceedings of the 15th European Conference on E-Learning",
publisher = "ACPI (Academic Conference Publishing International)",
url = "http://www.academic-conferences.org/conferences/ecel/ecel-future-and-past/",

}

RIS

TY - GEN

T1 - Validating a social media typology with machine learning and focus groups

AU - Saward, Guy

AU - Jefferies, Amanda

N1 - This document is the Accepted Manuscript of the following paper: Guy Saward and Amanda Jefferies, ‘Validating a social media typology with machine learning and focus groups’, in Proceedings of the 15th European Conference on E-Learning. Prague, Czech Republic 27-28 October 2016. Jarmila Novotna and Antonin Jancarik eds., ISBN 978-1-911218-18-0, e-ISBN 978-1-911218-17-3. Published by Academic Conference Publishing International (ACPI).

PY - 2016/10/26

Y1 - 2016/10/26

N2 - Social media networks (SMN) are an established part of the learning landscape in which our students reside as digital inhabitants. Our work is built around an ongoing four-year survey of student attitudes and engagement with SMN and their educational use. Our pre-conceptions were that students would be less keen on engaging with staff via social media. However, the survey results showed only 14% of students against this. Using machine learning to investigate whether those for academic SMN use (dubbed “integrationists”) could be separated from those against (“separatists”) showed it was hard to predict students’ attitudes purely based on their patterns of use of SMN.The complexity of the issues is reflected by focus group work that identified SMN as just one part of a complex pattern of personal communication. For some, Facebook (FB) consumed more time compared to text/email, but the latter were seen as more privileged with use restricted to higher value conversations and participants. Other insights included conflicted views on the value of SMN, a functional view of SMN alerts, and the lack of immersion in academic SMNs. These results suggest SMN are not a panacea for student engagement. Care must be taken in designing effective learning conversations using appropriate media and interaction. Slavishly adopting social practices from SMN will not automatically benefit learners and may leave them more disengaged and distracted than ever

AB - Social media networks (SMN) are an established part of the learning landscape in which our students reside as digital inhabitants. Our work is built around an ongoing four-year survey of student attitudes and engagement with SMN and their educational use. Our pre-conceptions were that students would be less keen on engaging with staff via social media. However, the survey results showed only 14% of students against this. Using machine learning to investigate whether those for academic SMN use (dubbed “integrationists”) could be separated from those against (“separatists”) showed it was hard to predict students’ attitudes purely based on their patterns of use of SMN.The complexity of the issues is reflected by focus group work that identified SMN as just one part of a complex pattern of personal communication. For some, Facebook (FB) consumed more time compared to text/email, but the latter were seen as more privileged with use restricted to higher value conversations and participants. Other insights included conflicted views on the value of SMN, a functional view of SMN alerts, and the lack of immersion in academic SMNs. These results suggest SMN are not a panacea for student engagement. Care must be taken in designing effective learning conversations using appropriate media and interaction. Slavishly adopting social practices from SMN will not automatically benefit learners and may leave them more disengaged and distracted than ever

KW - social media networks

KW - student engagement

KW - academic engagement

M3 - Conference contribution

SN - 978-1-911218-18-0

SP - 640

EP - 649

BT - Proceedings of the 15th European Conference on E-Learning

A2 - Novotna, Jarmila

A2 - Jancarik, Antonin

PB - ACPI (Academic Conference Publishing International)

CY - Reading, UK

T2 - ECEL 2016

Y2 - 27 October 2016 through 28 October 2016

ER -