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Can SQ and EQ values and their difference indicate programming aptitude to reduce dropout rate?

  • University of Latvia

Zinātniskās darbības rezultāts: Nodaļa grāmatā/enciklopēdijā/konferences krājumā › Konferences zinātniskais raksts › Pētniecība › koleģiāli recenzēts

5 Atsauces (Scopus)

Kopsavilkums

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.

OriģinālvalodaAngļu
Publikācijas avota nosaukumsNew Trends in Databases and Information Systems - ADBIS 2017 Short Papers and Workshops AMSD, BigNovelTI, DAS, SW4CH, DC, Proceedings
RedaktoriJerome Darmont, Marite Kirikova, Kjetil Norvag, Robert Wrembel, George A. Papadopoulos, Johann Gamper, Stefano Rizzi
IzdevējsSpringer Verlag
Lapas285-293
Lapu skaits9
ISBN (Drukātā versija)9783319671611
DOIs
Publikācijas statussPublicēts - 2017
Pasākums21st 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 - Nicosia, Kipra
Ilgums: 24 sept. 2017 → 27 sept. 2017

Publikāciju sērijas

NosaukumsCommunications in Computer and Information Science
Sējums767
ISSN (Drukātā versija)1865-0929

Konference

Konference21st 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
Valsts/TeritorijaKipra
PilsētaNicosia
Periods24/09/17 → 27/09/17

Nospiedums

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