Gender neutrality improved completion rate for all

Svedin, Maria; Bälter, Olle

doi:10.1080/08993408.2016.1231469

Cited by 11 publications

(4 citation statements)

References 36 publications

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“…This is an open access article distributed under the terms of the Creative Commons CC-BY License (http://creativecommons.org/licenses/by-nc/4.0/). al., 2013; Svedin & Bälter, 2016). Another study showed the short study approach scales to be associated with different information-seeking behaviors in a mixed sample of master's degree students (Heinström, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…The short version of the ASSIST has been used in research on students with mixed discipline backgrounds (Heinström, 2005) and on students within fields like medicine (Feeley & Biggerstaff, 2015;Liew, 2015), nursing (Martyn, Terwijn, Kek, & Huijser, 2014), psychology (Prat-Sala & Redford, 2010 and mathematics and computer science (Bälter, Cleveland-Innes, Petterson, Scheja, & Svedin, 2013;Svedin & Bälter, 2016). Heinström (2005) reported that the short scales correlate strongly with the respective full scales (strategic scales: r =0.91; deep and surface scales: r = 0.93).…”

Section: Introductionmentioning

confidence: 99%

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Psychometric Properties of the Short ASSISTScales

Bonsaksen¹

2018

Uniped

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Background: The shortening of measurement scales may improve their feasibility, but may also affect the scales' measurement properties. This study investigated the psychometric properties of the short Norwegian Approaches and Study Skills Inventory for Students (ASSIST) among occupational therapy students.Methods: The students (n = 148) completed the Norwegian ASSIST and provided sociodemographic data. Scale structure was examined with Principal Components Analysis (PCA). Scale consistency was assessed with Cronbach's α. Bivariate associations between the full and short scales were examined with Pearson's r. Linear regression analyses were used to assess associations between scale scores and the students' average exam grade.Results: Three factors were confirmed, but one item did not fit within the deep approach scale. Cronbach's α for the scales ranged 0.64-0.71. The full-length scales were strongly associated with the corresponding short scales, r ranging 0.85-0.87. For the surface scales, the full-length and short scale scores were both associated with the students' average exam grade. For the strategic scale, only the full-length scale scores were associated with exam grade.Conclusions: The short scales of the Norwegian ASSIST have satisfactory psychometric properties and represent a feasible way of assessing students' study approaches in Norwegian higher education.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Psychometric Properties of the Short ASSISTScales

Bonsaksen¹

2018

Uniped

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“…This is partly due to the selection process, but also due to the fact that computer science is not connoted as a male occupation in many non-Western cultures [30]. For a longer discussion on computer science and gender, see [31].…”

Section: Discussionmentioning

confidence: 99%

Effective Reskilling of Foreign-Born People at Universities - The Software Development Academy

et al. 2022

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Contribution: An intensive three-month educational program can be used for rapid integration of foreign-born people into the IT industry. A novel method for integrating industrial needs with the practical parts of a bachelor's Computer Science program. Background: The program was motivated by (1) the societal need to increase the meaningful integration of immigrants into the workforce, and (2) the demand for IT specialists in the IT labor market. Intended outcomes: An effective intensive software developer program with a high level of industrial integration and a working matching model for employment. Application design: The program consists of three different phases; recruitment of participants, training and job matching. The training is divided into six modules using five different teaching methods. An evaluation model, based on passive and active data, is implemented with fast learning loops for teachers and participants. Findings: The program has been run seven times with 263 unemployed participants of different nationalities. On average 82.6 percent of the participants found employment in the IT industry within 5 months of the course ending. Female participants are in the majority and are more successful in securing employment. The findings suggest that it was possible to rapidly prototype and deliver an advanced reskilling program within a university setting and use it as a positive method to support newcomers find meaningful work that has a direct benefit for the local IT industry, as well as for the wider society.

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“…Since disciplines such as computer sciences are preferred mostly by males, there is a difference in the feeling of efficacy in terms of gender other than the individuals' existing skills and performances. In addition, there is a prejudiced difference had been reported in terms of males and females from an external perspective (Byrne & Lyons, 2001;Svedin & Balter , 2016).…”

Section: Theoretical Background Individual Differences: Social and Comentioning

confidence: 99%

Individual Differences in Learning Computer Programming: A Social Cognitive Approach

Akar

Altun

2017

CONTEMP EDUC TECHNOL

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The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been conducted with 129 2nd year undergraduate students, who have taken Programming Languages-I course from three universities. Spatial ability has been measured through mental rotation and spatial visualization tests; working memory has been attained through the measurement of two sub-dimensions; visual-spatial and verbal working memory. Data were analyzed through Boosted Regression Trees and Random Forests, which are non-parametric predictive data mining techniques. The analyses yielded a user model that would predict students' computer programming performance based on various social and cognitive variables. The results yielded that the variables, which contributed to the programming performance prediction significantly, were spatial orientation skill, spatial memory, mental orientation, self-efficacy perception and verbal memory with equal importance weights. Yet, the effect of prior knowledge and gender on programming performance has not been found to be significant. The importance of ranks of variables and the proportion of predicted variance of programming performance could be used as guidelines when designing instruction and developing curriculum.

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Gender neutrality improved completion rate for all

Cited by 11 publications

References 36 publications

Psychometric Properties of the Short ASSISTScales

Psychometric Properties of the Short ASSISTScales

Effective Reskilling of Foreign-Born People at Universities - The Software Development Academy

Individual Differences in Learning Computer Programming: A Social Cognitive Approach

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