Skip navigation
User training | Reference and search service

Library catalog

Integrated Search
Content aggregators
Please use this identifier to cite or link to this item:

Title: Unfolding the drivers of students’ success in answering multiple-choice questions about Microsoft Excel
Authors: Moro, S.
Martins, A.
Ramos, P.
Esmerado, J.
Costa, J. M.
Almeida, D.
Keywords: Data mining
Feature relevance
Multiple-choice questions
Students’ performance
Issue Date: 2020
Publisher: Taylor and Francis
Abstract: Many university programs include Microsoft Excel courses given their value as a scientific and technical tool. However, evaluating what is effectively learned by students is a challenging task. Considering multiple-choice written exams are a standard evaluation format, this study aimed to uncover the features influencing students’ success in answering these types of questions. The empirical experiments were based on Excel evaluation exams containing questions answered by 526 students between 2012 and 2016, with a total of 3,340 answers characterized by 17 features. Through data mining, a neural network was developed that accurately modeled students’ choices. A sensitivity analysis was applied to the model to assess the most relevant features. Findings identified four highly relevant features for students’ success: number of words of the question, topic, difficulty degree, and number of similar choices. This study helps to guide the design of future exams by quantifying the individual influence of each feature.
Peer reviewed: yes
DOI: 10.1080/07380569.2020.1749127
ISBN: 1528-7033
ISSN: 0738-0569
Accession number: WOS:000526346300001
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

Files in This Item:
There are no files associated with this item.

FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Currículo DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.