TY - GEN
T1 - Can SQ and EQ values and their difference indicate programming aptitude to reduce dropout rate?
AU - Borzovs, Juris
AU - Kozmina, Natalija
AU - Niedrite, Laila
AU - Solodovnikova, Darja
AU - Straujums, Uldis
AU - Zuters, Janis
AU - Klavins, Atis
N1 - Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - A crucial problem that we are currently facing at the Faculty of Computing of the University of Latvia is that during the first study semester on average 30% of the first-year students drop out, whereas after the first year of studies the number of dropouts increases up to nearly 50%. Thus, our overall goal is to determine in advance applicants that most likely will not finish the first study year successfully. A hypothesis formulated in another research study was that programming aptitude could be predicted based on the results of two personality self-report questionnaires − Systemizing Quotient (SQ) and Empathy Quotient (EQ) − taken by students. The difference between the SQ and EQ scores had a strong correlation with grades received for programming test. We reproduced the circumstances of mentioned empirical study with our first-year students using similar tests to calculate SQ and EQ, and semester grades in introductory programming course as a quantitative measure to evaluate programming ability. In this paper, we elaborate on the empirical setting, measures, and estimation methods of our study, which produced the results that made us call the stated hypothesis into question and disprove it.
AB - A crucial problem that we are currently facing at the Faculty of Computing of the University of Latvia is that during the first study semester on average 30% of the first-year students drop out, whereas after the first year of studies the number of dropouts increases up to nearly 50%. Thus, our overall goal is to determine in advance applicants that most likely will not finish the first study year successfully. A hypothesis formulated in another research study was that programming aptitude could be predicted based on the results of two personality self-report questionnaires − Systemizing Quotient (SQ) and Empathy Quotient (EQ) − taken by students. The difference between the SQ and EQ scores had a strong correlation with grades received for programming test. We reproduced the circumstances of mentioned empirical study with our first-year students using similar tests to calculate SQ and EQ, and semester grades in introductory programming course as a quantitative measure to evaluate programming ability. In this paper, we elaborate on the empirical setting, measures, and estimation methods of our study, which produced the results that made us call the stated hypothesis into question and disprove it.
KW - Correlation
KW - Dropout rate
KW - Empathy quotient
KW - Programming aptitude
KW - Systemizing quotient
UR - https://www.scopus.com/pages/publications/85029793417
U2 - 10.1007/978-3-319-67162-8_28
DO - 10.1007/978-3-319-67162-8_28
M3 - Conference paper
AN - SCOPUS:85029793417
SN - 9783319671611
T3 - Communications in Computer and Information Science
SP - 285
EP - 293
BT - New Trends in Databases and Information Systems - ADBIS 2017 Short Papers and Workshops AMSD, BigNovelTI, DAS, SW4CH, DC, Proceedings
A2 - Darmont, Jerome
A2 - Kirikova, Marite
A2 - Norvag, Kjetil
A2 - Wrembel, Robert
A2 - Papadopoulos, George A.
A2 - Gamper, Johann
A2 - Rizzi, Stefano
PB - Springer Verlag
T2 - 21st European Conference on Advances in Databases and Information Systems, ADBIS 2017 and 1st workshop on Data Driven Approaches for Analyzing and Managing Scholarly Data, AMSD 2017, 1st workshop on Novel Techniques for Integrating Big Data, BigNovelTI 2017, 1st International workshop on Data Science: Methodologies and Use-Cases, DaS 2017, 2nd International workshop on Semantic Web for Cultural Heritage, SW4CH 2017
Y2 - 24 September 2017 through 27 September 2017
ER -