International internships and employability: a game-based assessment approach

Predovic, Dolly; Dennis, John L.; Jones, Elspeth

doi:10.1080/07294360.2021.1889994

Cited by 13 publications

(8 citation statements)

References 45 publications

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“…On the other hand, only a few of the reviewed studies (i.e., six) suggest that traineeships abroad may influence participants' cognitive processes and strategies. These report that students increased their problem‐solving skills (Flander & Korada, 2020; Ito & Igano, 2021; Giannopoulou et al, 2020), their critical thinking skills (Flander & Korada, 2020; Ito & Igano, 2021; Zierer, 2017), their analytical thinking skills (Moise et al, 2013), and their learning agility (Predovic et al, 2021). Similarly, a small number of the reviewed studies (i.e., five) document an improvement in creativity following participation in international internships.…”

Section: Resultsmentioning

confidence: 99%

“…Also, in Snodgrass et al (2021) participants in an international internship programme are scored on a Cultural Intelligence Scale (CIS). An alternative approach still relying on non-self-reported outcome measures, though different from those based on the results of formal tests, is adopted by Predovic et al (2021). They use a game-based tool to examine One should also note that none of the studies included in the review and based on surveys/interviews addresses problems arising from an endogenous participation decision.…”

Section: Methodological Problemsmentioning

confidence: 99%

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International internships and skill development: A systematic review

Pietro

2022

Review of Education

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An increasing number of students complete an internship during their higher education studies in a country different from that of their home institution. A main advantage of this type of mobility is that it responds to employers' need for graduates with both hands‐on experience and global skills. In this paper, we attempt to review existing research on the types of skills higher education students gain through their participation in international internships. While there are several systematic reviews on study abroad programmes, this is, to the best of our knowledge, the first focusing on internship programmes abroad. Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) approaches were used to explore four electronic databases (Scopus, Google Scholar, ScienceDirect and Resources Information Center). From these, 31 relevant studies were identified, and data were examined using a combination of thematic and content analysis. Intrapersonal skills (e.g., open mindedness, self‐confidence) are found to be the most frequently cited skills learned by participants. Many of the reviewed studies also report learning gains in terms of practical knowledge and language proficiency. On the other hand, there is less evidence suggesting that international internships enhance cognitive skills and leadership skills. The large majority of the reviewed studies, however, have methodological problems. A future research agenda is outlined, along with suggestions for improving the research methodology.

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Section: Resultsmentioning

confidence: 99%

Section: Methodological Problemsmentioning

confidence: 99%

International internships and skill development: A systematic review

Pietro

2022

Review of Education

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“…Predovic et al [26] have suggested that a tool for game-based analytics are used to predict behaviours linked to employability skills in order to measure employability after domestic and international internships. The underlying relationships between 33 behavioural descriptors which assess traits like assiduity, social intelligence, learning agility, leadership, and logical reasoning were investigated using exploratory factor analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of Student Employability through Internship based on Big Data Analysis

Yubin Wang

2024

jes

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The internship course is among the most important because it gives students a hands-on opportunity to apply their knowledge and get ready to launch a professional career. Internships, yet, don't ensure employability, particularly in cases where a graduate's performance is subpar and internship requirements are not fulfilled. Researchers in the field of higher education face a significant challenge in predicting employability due to the multitude of factors that contribute to this issue. This research presented the methodology for more accurately classifying student data in order to overcome this drawback. Online surveys were used to collect data from Princess Nourahbint Abdulrahman University's College of Computer and Information Sciences information systems (IS) graduates (PNU). The Switching Hierarchical Gaussian Filter (SHGF) is used to preprocess the data at the pre-processing stage. The outcome from the pre-processing is transferred to the feature selection method, which uses Siberian Tiger Optimization (STO) to select the student features. The employed, continuing studies, unemployed, and training are successfully classified using the Multi Fidelity Deep Neural Network. The proposed MFDNN -STO applied to the MATLAB/Simulink platform. To calculate the proposed approach, performance metrics including recall, ROC, computation time, accuracy, precision, sensitivity, and F-score were examined. Higher accuracy of 16.65%, 18.85%, and 17.89%, as well as higher sensitivity of 16.34%, 12.23%, and 18.54%, are achieved by the suggested MFDNN-STO method. The computation time was reduced by 14.89%, 16.89%, and 18.23% as well as 82.37%, 94.47%, and 87.76% in comparison to the existing method.

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“…The question to be answered is "Can the game mechanic that promotes such learning be cataloged" [18]. This is because teachers do not only depend on 1 type of teaching but a combination of many [23], [24]. As a result, a successful model must be interoperable.…”

Section: High-order Thinking Through Bloom's Taxonomymentioning

confidence: 99%

Improving Digital Game-based Learning Assessment to Acquire High-Order Thinking Skills Using Bloom’s Taxonomy

Kgosietsile

2023

IJICR

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The 21 st century skills require learners to master high-order thinking skills (HOTS). High-order thinking is a cognitive process that involves a complex understanding of information beyond just memorizing and recalling. It covers complex problem-solving, critical thinking, generating new information, and synthesizing it. Traditional methods are known to induce test anxiety and ignore the learner's thinking processes. This low-order process of memorizing and understanding information is decontextualized and does not lead to deep knowledge. Student assessment should not only be concerned with what students know but rather what they can do with the knowledge they have acquired. These needed skills can be developed and improved through practical models such as game-based learning. Games can ensure HOTS; however, it is uncertain how they assess and evaluate learner performance. Initially, students were given a test before and after game play to gauge how much they knew before and after learning. To assess HOTS we need robust assessment mechanisms embedded within game applications to measure performance throughout gameplay. Therefore, research needs to explore how HOTS is measured in pedagogical games. The ability of games to quantify data for scoring cannot be doubted, however little is known particularly in the context of grading, results analysis, and implementing assessment strategies. Empirical studies are still lacking. We reviewed digital game-based learning assessment's (DGBLA) capacity to evaluate and improve high-order thinking. Authoritative databases were analyzed and compared, Web of Science and Scopus emerged best, giving 32 literature sources. The study found that game assessment structured through Bloom's Taxonomy improves HOTS.

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International internships and employability: a game-based assessment approach

Cited by 13 publications

References 45 publications

International internships and skill development: A systematic review

International internships and skill development: A systematic review

Prediction of Student Employability through Internship based on Big Data Analysis

Improving Digital Game-based Learning Assessment to Acquire High-Order Thinking Skills Using Bloom’s Taxonomy

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