Learning About Learning at Scale: Methodological Challenges and Recommendations

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Learning About Learning at Scale : Methodological Challenges and Recommendations. / van der Sluis, Frans; van der Zee, Tim; Ginn, Jasper.

Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. New York, NY, USA : ACM, 2017. p. 131-140 (L@S '17).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

van der Sluis, F, van der Zee, T & Ginn, J 2017, Learning About Learning at Scale: Methodological Challenges and Recommendations. in Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. ACM, New York, NY, USA, L@S '17, pp. 131-140. https://doi.org/10.1145/3051457.3051461

APA

van der Sluis, F., van der Zee, T., & Ginn, J. (2017). Learning About Learning at Scale: Methodological Challenges and Recommendations. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale (pp. 131-140). ACM. L@S '17 https://doi.org/10.1145/3051457.3051461

Vancouver

van der Sluis F, van der Zee T, Ginn J. Learning About Learning at Scale: Methodological Challenges and Recommendations. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. New York, NY, USA: ACM. 2017. p. 131-140. (L@S '17). https://doi.org/10.1145/3051457.3051461

Author

van der Sluis, Frans ; van der Zee, Tim ; Ginn, Jasper. / Learning About Learning at Scale : Methodological Challenges and Recommendations. Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. New York, NY, USA : ACM, 2017. pp. 131-140 (L@S '17).

Bibtex

@inproceedings{297da20de91e46598391db43cd756dec,
title = "Learning About Learning at Scale: Methodological Challenges and Recommendations",
abstract = "Learning at scale opens up a new frontier to learn about learning. MOOCs and similar large-scale online learning platforms give an unprecedented view of learners' behavior whilst learning. In this paper, we argue that the abundance of data that results from such platforms not only brings novel opportunities to the study of learning, but also bears novel methodological challenges. We show that the resulting data comes with various challenges with respect to the granular, observational, and large nature of these data. Additionally, we discuss a series of potential solutions, such as sharing validated models and performing pre-registered confirmatory research. With these contributions, this paper aims to increase awareness and understanding of both the strengths and challenges of research on learning at scale.",
keywords = "behavioral traces, big data, learning analytics, online learning, research methodology, research validity",
author = "{van der Sluis}, Frans and {van der Zee}, Tim and Jasper Ginn",
year = "2017",
doi = "10.1145/3051457.3051461",
language = "Udefineret/Ukendt",
isbn = "978-1-4503-4450-0",
series = "L@S '17",
publisher = "ACM",
pages = "131--140",
booktitle = "Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale",

}

RIS

TY - GEN

T1 - Learning About Learning at Scale

T2 - Methodological Challenges and Recommendations

AU - van der Sluis, Frans

AU - van der Zee, Tim

AU - Ginn, Jasper

PY - 2017

Y1 - 2017

N2 - Learning at scale opens up a new frontier to learn about learning. MOOCs and similar large-scale online learning platforms give an unprecedented view of learners' behavior whilst learning. In this paper, we argue that the abundance of data that results from such platforms not only brings novel opportunities to the study of learning, but also bears novel methodological challenges. We show that the resulting data comes with various challenges with respect to the granular, observational, and large nature of these data. Additionally, we discuss a series of potential solutions, such as sharing validated models and performing pre-registered confirmatory research. With these contributions, this paper aims to increase awareness and understanding of both the strengths and challenges of research on learning at scale.

AB - Learning at scale opens up a new frontier to learn about learning. MOOCs and similar large-scale online learning platforms give an unprecedented view of learners' behavior whilst learning. In this paper, we argue that the abundance of data that results from such platforms not only brings novel opportunities to the study of learning, but also bears novel methodological challenges. We show that the resulting data comes with various challenges with respect to the granular, observational, and large nature of these data. Additionally, we discuss a series of potential solutions, such as sharing validated models and performing pre-registered confirmatory research. With these contributions, this paper aims to increase awareness and understanding of both the strengths and challenges of research on learning at scale.

KW - behavioral traces, big data, learning analytics, online learning, research methodology, research validity

U2 - 10.1145/3051457.3051461

DO - 10.1145/3051457.3051461

M3 - Konferencebidrag i proceedings

SN - 978-1-4503-4450-0

T3 - L@S '17

SP - 131

EP - 140

BT - Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale

PB - ACM

CY - New York, NY, USA

ER -

ID: 212266393