Expectation Differences Between Students and Staff of Using Learning Analytics in Finnish Universities

Okkonen, Jussi; Helle, Tanja; Lindsten, Hanna

doi:10.1007/978-3-030-40690-5_38

Cited by 5 publications

(14 citation statements)

References 6 publications

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“…Extensive implementation of data driven management has been executed during the last decade. Okkonen, Helle and Lindsten [1] point out the dichotomy, i.e. difference on managerial perspective, in expectations as students and teachers seek to manage daily activities on micro-level, but those in managerial position seek extensive leverage effect on meso-and macro-levels.…”

Section: Introductionmentioning

confidence: 99%

“…Ifenthaler and Schumacher [2] have approached student sentiments on learning analytics from privacy perspective. Okkonen et al [1] addresses the same issue by the expectation differences between students and other users. There seems to be certain privacy principles that are universal.…”

Section: Introductionmentioning

confidence: 99%

“…The students seem to have need to have certain amount of privacy even their data is stored, analyzed, distributed and used in learning analytics systems and processes. Privacy refers to remaining anonymous to unknown as stated in [1] and [2]. Ifenthaler and Schumaher [2] also underline difference between private and public in sense the data about personal matters is private and data related to studying is public for official use.…”

Section: Introductionmentioning

confidence: 99%

“…Especially when analytics is implemented in full extension the privacy issue, or how my data is used, takes new form. As presented in Okkonen et al [1] roughly 50 % of the students were willing to receive benchmarking or other algorithm powered data on their performance. This reflects to finding that university students considered themselves as part of academic community, not raw material, refined for the needs of the society.…”

Section: Introductionmentioning

confidence: 99%

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Ethical Considerations on Using Learning Analytics in Finnish Higher Education

Okkonen

Helle

Lindsten

2020

Advances in Intelligent Systems and Computing

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Utilization of learning analytics in universities is complex setting and there are several issues on motives, expectations and insights on ethics There is lack of critical literature as the whole topic on learning analytics is still mostly addressed from the perspective of analytics per se. Current literature draws idealistic picture of well-functioning apparatus that supports studying process, enhances learning out-comes and eases the managerial burden and contradictions, even conflicts on utilizing learning analytics are only marginally discussed.. The discussion on ethics of using learning analytics is spawns from the different practical and ideological issues regarding learning analytics. Taking the perspectives of privacy, ownership of data, and how studies are managed there are differences on expectations among the students and personnel. The aim of this paper is to examine and discuss the dissonance between expectations and hopes on ethical conduct of learning analytics in Finnish universities. The analysis is based on open ended replies of a survey collected among Finnish university students and staff in spring 2019.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Ethical Considerations on Using Learning Analytics in Finnish Higher Education

Okkonen

Helle

Lindsten

2020

Advances in Intelligent Systems and Computing

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“…The fourth trend is compliance, privacy, and security issues on the level mentioned and can be considered as the primary prerequisite for utilising learning analytics. [1] In information technology and communication (ITC) industry the technology advances are unexpected and moving mysterious ways causing significant mismatch between demand and supply in labour market. To some extent the mismatch is due to emergence of new technologies replacing the old ones.…”

mentioning

confidence: 99%

Using AI to Decrease Demand and Supply Mismatch in ITC Labour Market

Okkonen

Ketamo

Lindsten

et al. 2020

Advances in Intelligent Systems and Computing

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In information technology and communication (ITC) industry the technology advances are unexpected and moving mysterious ways causing significant mismatch between demand and supply in labour market. To some extent the mismatch is due to emergence of new technologies replacing the old ones. On the other hand, it is also due to lack of capability and capacity of educational system to provide up to date and spot on graduates. There are several attempts to bridge the gap between supply and demand, yet both public and private sector had at least partially failed in the task.This paper presents a novel AI driven modus operandi that provides students or persons already in labour market a way to match one's competencies against existing or future competency requirements, and thus being valid employee or applicant. On the other hand, the service discussed in the paper is also tool for giving input for forecasting future labour needs. And the third, the service also serves as mid-and long-range planning apparatus for education provider when making decisions on what academic modules best serve the needs of society and individuals. The paper presents the concept of technology and functionalities as well as roadmap for developing and implementing the service. The presented concept is heuristically proofed in expert evaluation. Moreover, the heart of the service has been technically and functionally tested in several cases. At the conclusion the paper presents model for matching system for labour competency development. The issues related to implementation and the next steps are also discussed.

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