Bibliographic record
Abstract
Information and communications technology (ICT) has been changing rapidly over a long period and this rate of change is likely to continue or increase (Benamati & Lederer, 2001a; Lee & Xia, 2005). This rapid rate of change has produced many opportunities for organizations, but has also brought with it many challenges (Benamati & Lederer, 2001b). Among these challenges is the struggle for organizations to obtain personnel with the appropriate information technology (IT) knowledge and skills in order to meet their ICT needs (Byrd & Turner, 2001; Doke, 1999; Standbridge & Autrey, 2001). This is mirrored by the continual requirement for IT professionals to keep up to date with the skills required by organizations (Benamati et al., 2001a; Klobas & McGill, 1993; Moore, 2000). Previous research has investigated the importance employers place on various skills and perceived deficiencies in these skills (e.g., Doke, 1999; Leitheiser, 1992; Nelson, 1991; Prabhakar, Litecky, & Arnett, 2005). While the call for improved communication and social skills has been consistent, the technical skills in demand have varied dramatically over time (Prabhakar et al., 2005; Van Slyke, Kittner, & Cheney, 1998). Less has been written about students’ perceptions of the importance of various ICT skills, though this was addressed in a study that compared Australian and American students’ perceptions of ICT job skills (von Hellens, Van Slyke, & Kittner, 2000). This article provides an overview of a project that investigated the channels of information that ICT students use to keep up to date with employers’ needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".