Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography

Justine Maclean; Dragan Gasevic; Yi-Shan Tsai; Natasa Pantic; Ana Hibert; Michael R. Phillips

Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography

Justine Maclean, Dragan Gasevic, Yi-Shan Tsai, Natasa Pantic, Ana Hibert, Michael R. Phillips

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

This paper outlines a virtual internship designed to provide trainee teachers with opportunities for experiential learning by engaging them in authentic school situations. Using epistemic network analysis, data collected from the virtual internship will help us understand the development of relational agency among teachers and characteristics of an inclusive learning community.

Original language	English
Title of host publication	International Conference on Quantitative Ethnography
Subtitle of host publication	Conference Proceedings
Editors	C Damşa, A Barany
Publisher	The International Society for Quantitative Ethnography
Chapter	10
Pages	45-49
Number of pages	5
Publication status	Published - 15 Oct 2022

Keywords / Materials (for Non-textual outputs)

agency
virtual internship
epistemic network analysis

Cite this

Maclean, J., Gasevic, D., Tsai, Y.-S., Pantic, N., Hibert, A., & Phillips, M. R. (2022). Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography. In C. Damşa, & A. Barany (Eds.), International Conference on Quantitative Ethnography: Conference Proceedings (pp. 45-49). The International Society for Quantitative Ethnography.

Maclean, Justine ; Gasevic, Dragan ; Tsai, Yi-Shan et al. / Researching relational agency and inclusive learning communities through a virtual internship : The International Society for Quantitative Ethnography. International Conference on Quantitative Ethnography: Conference Proceedings . editor / C Damşa ; A Barany. The International Society for Quantitative Ethnography, 2022. pp. 45-49

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title = "Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography",

abstract = "This paper outlines a virtual internship designed to provide trainee teachers with opportunities for experiential learning by engaging them in authentic school situations. Using epistemic network analysis, data collected from the virtual internship will help us understand the development of relational agency among teachers and characteristics of an inclusive learning community.",

keywords = "agency, virtual internship, epistemic network analysis",

author = "Justine Maclean and Dragan Gasevic and Yi-Shan Tsai and Natasa Pantic and Ana Hibert and Phillips, {Michael R.}",

year = "2022",

month = oct,

day = "15",

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pages = "45--49",

editor = "C Dam{\c s}a and A Barany",

booktitle = "International Conference on Quantitative Ethnography",

publisher = "The International Society for Quantitative Ethnography",

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Maclean, J, Gasevic, D, Tsai, Y-S, Pantic, N, Hibert, A & Phillips, MR 2022, Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography. in C Damşa & A Barany (eds), International Conference on Quantitative Ethnography: Conference Proceedings . The International Society for Quantitative Ethnography, pp. 45-49.

Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography. / Maclean, Justine; Gasevic, Dragan; Tsai, Yi-Shan et al.
International Conference on Quantitative Ethnography: Conference Proceedings . ed. / C Damşa; A Barany. The International Society for Quantitative Ethnography, 2022. p. 45-49.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Researching relational agency and inclusive learning communities through a virtual internship

T2 - The International Society for Quantitative Ethnography

AU - Maclean, Justine

AU - Gasevic, Dragan

AU - Tsai, Yi-Shan

AU - Pantic, Natasa

AU - Hibert, Ana

AU - Phillips, Michael R.

PY - 2022/10/15

Y1 - 2022/10/15

N2 - This paper outlines a virtual internship designed to provide trainee teachers with opportunities for experiential learning by engaging them in authentic school situations. Using epistemic network analysis, data collected from the virtual internship will help us understand the development of relational agency among teachers and characteristics of an inclusive learning community.

AB - This paper outlines a virtual internship designed to provide trainee teachers with opportunities for experiential learning by engaging them in authentic school situations. Using epistemic network analysis, data collected from the virtual internship will help us understand the development of relational agency among teachers and characteristics of an inclusive learning community.

KW - agency

KW - virtual internship

KW - epistemic network analysis

UR - https://www.qesoc.org/images/pdf/ICQE22_proceedings_supplement.pdf

M3 - Conference contribution

SP - 45

EP - 49

BT - International Conference on Quantitative Ethnography

A2 - Damşa, C

A2 - Barany, A

PB - The International Society for Quantitative Ethnography

ER -

Maclean J, Gasevic D, Tsai YS, Pantic N, Hibert A, Phillips MR. Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography. In Damşa C, Barany A, editors, International Conference on Quantitative Ethnography: Conference Proceedings . The International Society for Quantitative Ethnography. 2022. p. 45-49

Researching relational agency and inclusive learning communities through a virtual internship: The International Society for Quantitative Ethnography

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

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Cite this