Aspect-based Sentiment Analysis for University Teaching Analytics

Tim Schurig; Sine Zambach; Raghava Rao Mukkamala; Malte Petry

Aspect-based Sentiment Analysis for University Teaching Analytics

Tim Schurig, Sine Zambach, Raghava Rao Mukkamala, Malte Petry

Department of Digitalization

Freie Universität Berlin

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

Abstract

Aspect-based sentiment analysis (ABSA) is a natural language processing method to analyze sentiments from large amounts of unstructured text in a much more fine-grained manner at the aspect level. In this research work, we apply it to analyze open text replies from surveys regarding online teaching. Like most other educational institutions, Copenhagen Business School (CBS) had to shift to online teaching from one day to the next. Using ABSA, we investigated the impact of this forced online learning experiment on teaching quality in the spring semester of 2020. Our findings reveal that students disliked online teaching due to insufficient information and unadjusted teaching methods. However, students liked its flexibility and possibility to learn at an individual pace. We show that ABSA can extract valuable information in an easily interpretable manner to support teaching and learning processes. Finally, our findings show that ABSA is a valuable tool to analyze unstructured text quantitatively.

Original language	English
Title of host publication	Proceedings of the 30th European Conference on Information Systems (ECIS)
Number of pages	18
Place of Publication	Atlanta, GA
Publisher	Association for Information Systems. AIS Electronic Library (AISeL)
Publication date	2022
Article number	135
Publication status	Published - 2022
Event	The 30th European Conference on Information Systems (ECIS) 2022: New Horizons in Digitally United Societies - Universitatea de Vest din Timișoara (UVT) / West University of Timişoara (WUT), Timisoara, Romania Duration: 19 Jun 2022 → 24 Jun 2022 Conference number: 30 https://ecis2022.eu/

Conference

Conference	The 30th European Conference on Information Systems (ECIS) 2022
Number	30
Location	Universitatea de Vest din Timișoara (UVT) / West University of Timişoara (WUT)
Country/Territory	Romania
City	Timisoara
Period	19/06/2022 → 24/06/2022
Internet address	https://ecis2022.eu/

Series	Proceedings of the European Conference on Information Systems
ISSN	0000-0034

Keywords

Aspect-based sentiment analysis
Natural language processing
Covid-19
Open text surverys
Online teaching

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Cite this

@inproceedings{6acdf81b939845bab2953c79419f8a4c,

title = "Aspect-based Sentiment Analysis for University Teaching Analytics",

abstract = "Aspect-based sentiment analysis (ABSA) is a natural language processing method to analyze sentiments from large amounts of unstructured text in a much more fine-grained manner at the aspect level. In this research work, we apply it to analyze open text replies from surveys regarding online teaching. Like most other educational institutions, Copenhagen Business School (CBS) had to shift to online teaching from one day to the next. Using ABSA, we investigated the impact of this forced online learning experiment on teaching quality in the spring semester of 2020. Our findings reveal that students disliked online teaching due to insufficient information and unadjusted teaching methods. However, students liked its flexibility and possibility to learn at an individual pace. We show that ABSA can extract valuable information in an easily interpretable manner to support teaching and learning processes. Finally, our findings show that ABSA is a valuable tool to analyze unstructured text quantitatively.",

keywords = "Aspect-based sentiment analysis, Natural language processing, Covid-19, Open text surverys, Online teaching, Aspect-based sentiment analysis, Natural language processing, Covid-19, Open text surverys, Online teaching",

author = "Tim Schurig and Sine Zambach and Mukkamala, {Raghava Rao} and Malte Petry",

year = "2022",

language = "English",

series = "Proceedings of the European Conference on Information Systems",

booktitle = "Proceedings of the 30th European Conference on Information Systems (ECIS)",

publisher = "Association for Information Systems. AIS Electronic Library (AISeL)",

note = "The 30th European Conference on Information Systems (ECIS) 2022 : New Horizons in Digitally United Societies, ECIS2022 ; Conference date: 19-06-2022 Through 24-06-2022",

url = "https://ecis2022.eu/",

}

Schurig, T, Zambach, S , Mukkamala, RR & Petry, M 2022, Aspect-based Sentiment Analysis for University Teaching Analytics. in Proceedings of the 30th European Conference on Information Systems (ECIS)., 135, Association for Information Systems. AIS Electronic Library (AISeL), Atlanta, GA, Proceedings of the European Conference on Information Systems, The 30th European Conference on Information Systems (ECIS) 2022, Timisoara, Romania, 19/06/2022. <http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1134&context=ecis2022_rp>

Aspect-based Sentiment Analysis for University Teaching Analytics. / Schurig, Tim; Zambach, Sine ; Mukkamala, Raghava Rao et al.
Proceedings of the 30th European Conference on Information Systems (ECIS). Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL), 2022. 135 (Proceedings of the European Conference on Information Systems).

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

TY - GEN

T1 - Aspect-based Sentiment Analysis for University Teaching Analytics

AU - Schurig, Tim

AU - Zambach, Sine

AU - Mukkamala, Raghava Rao

AU - Petry, Malte

N1 - Conference code: 30

PY - 2022

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N2 - Aspect-based sentiment analysis (ABSA) is a natural language processing method to analyze sentiments from large amounts of unstructured text in a much more fine-grained manner at the aspect level. In this research work, we apply it to analyze open text replies from surveys regarding online teaching. Like most other educational institutions, Copenhagen Business School (CBS) had to shift to online teaching from one day to the next. Using ABSA, we investigated the impact of this forced online learning experiment on teaching quality in the spring semester of 2020. Our findings reveal that students disliked online teaching due to insufficient information and unadjusted teaching methods. However, students liked its flexibility and possibility to learn at an individual pace. We show that ABSA can extract valuable information in an easily interpretable manner to support teaching and learning processes. Finally, our findings show that ABSA is a valuable tool to analyze unstructured text quantitatively.

AB - Aspect-based sentiment analysis (ABSA) is a natural language processing method to analyze sentiments from large amounts of unstructured text in a much more fine-grained manner at the aspect level. In this research work, we apply it to analyze open text replies from surveys regarding online teaching. Like most other educational institutions, Copenhagen Business School (CBS) had to shift to online teaching from one day to the next. Using ABSA, we investigated the impact of this forced online learning experiment on teaching quality in the spring semester of 2020. Our findings reveal that students disliked online teaching due to insufficient information and unadjusted teaching methods. However, students liked its flexibility and possibility to learn at an individual pace. We show that ABSA can extract valuable information in an easily interpretable manner to support teaching and learning processes. Finally, our findings show that ABSA is a valuable tool to analyze unstructured text quantitatively.

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KW - Open text surverys

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KW - Aspect-based sentiment analysis

KW - Natural language processing

KW - Covid-19

KW - Open text surverys

KW - Online teaching

M3 - Article in proceedings

T3 - Proceedings of the European Conference on Information Systems

BT - Proceedings of the 30th European Conference on Information Systems (ECIS)

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