Automated Author ProfilePesonen, Erkki
Pesonen, Erkki
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students’ initial expectations of university study and career. This paper reports on a study of CS first-year students’ expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students’ eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.
Authors
- Kinnunen, Päivi ;
- Butler, Matthew ;
- Morgan, Michael ;
- Nylen, Aletta ;
- Anne-Kathrin Peters ;
- Sinclair, Jane ;
- Kalvala, Sara ;
- Pesonen, Erkki
There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students’ initial expectations of university study and career. This paper reports on a study of CS first-year students’ expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students’ eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.
Authors
- Kinnunen, Päivi ;
- Butler, Matthew ;
- Morgan, Michael ;
- Nylen, Aletta ;
- Anne-Kathrin Peters ;
- Sinclair, Jane ;
- Kalvala, Sara ;
- Pesonen, Erkki