Forward-Looking Activities Supporting Technological Planning of AI-Based Learning Platforms

Skulimowski, Andrzej M. J.

doi:10.1007/978-3-030-35758-0_26

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…The first stage of the survey was organized according to classical decision Delphi principles (Rauch, 1979), in multiround mode (Skulimowski, 2019). Hence, the which was quantified as {1,…, 5} for the subsequent analysis.…”

Section: The Methodology Of the Delphi Survey On Ailp Technologiesmentioning

confidence: 99%

“…The above consensus analysis validates the survey results and their further uses, which are presented in sections 3.2 and 3.3. For more details of the Delphi survey methodology, see Skulimowski (2019), and references therein.…”

Section: The Methodology Of the Delphi Survey On Ailp Technologiesmentioning

confidence: 99%

“…This trend matches the recent progress in artificial intelligence (AI) tools and technologies that support teaching and learning. Such systems are collectively referred to as AI-based learning platforms (AILPs) (Skulimowski, 2019), e-science (Hey & Trefethen, 2005), or open innovation platforms (Klein & Convertino, 2015). An AILP feature that can be achieved with appropriate AI tools is the stimulation and assessment of user creativity.…”

Section: Introductionmentioning

confidence: 99%

“…Current experimental learning technologies based on brain-computer interfaces (BCIs), virtual reality (VR), or augmented reality (AR) coupled with AI-based learning process tracking can encompass learners' creativity monitoring and stimulation. A recent Delphi survey (Skulimowski, 2019) shows that common deployment of the aforementioned human-computer communication channels in AILPs has already commenced and this trend is expected to grow in the coming decades. The impact of AI techniques on the software architecture of knowledge repositories, and trends in LMS development, including user creativity issues, is thus an important research area that merits indepth exploration.…”

Section: Introductionmentioning

confidence: 99%

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A future‐oriented approach to the selection of artificial intelligence technologies for knowledge platforms

Skulimowski

Köhler

2023

Asso for Info Science & Tech

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This article presents approaches used to solve the problem of selecting AI technologies and tools to obtain the creativity fostering functionalities of an innovative knowledge platform. The aforementioned selection problem has been lagging behind other software‐specific aspects of online knowledge platform and learning platform development so far. We linked technological recommendations from group decision support exercises to the platform design aims and constraints using an expert Delphi survey and multicriteria analysis methods. The links between expected advantages of using selected AI building tools, AI‐related system functionalities, and their ongoing relevance until 2030 were assessed and used to optimize the learning scenarios and in planning the future development of the platform. The selected technologies allowed the platform management to implement the desired functionalities, thus harnessing the potential of open innovation platforms more effectively and delivering a model for the development of a relevant class of advanced open‐access knowledge provision systems. Additionally, our approach is an essential part of digital sustainability and AI‐alignment strategy for the aforementioned class of systems. The knowledge platform, which serves as a case study for our methodology has been developed within an EU Horizon 2020 research project.

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Section: The Methodology Of the Delphi Survey On Ailp Technologiesmentioning

confidence: 99%

Section: The Methodology Of the Delphi Survey On Ailp Technologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A future‐oriented approach to the selection of artificial intelligence technologies for knowledge platforms

Skulimowski

Köhler

2023

Asso for Info Science & Tech

Self Cite

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“…e.g. Skulimowski et al , 2019, combined with expert panel meetings and outcomes of bibliometric and patentometric research proved most useful within the overall project. The analysis of expert responses was combined with an information retrieval strategy from the open Web and from major bibliographic databases.…”

Section: Introductionmentioning

confidence: 99%

Visions of a Future Research Workplace Arising from Recent Foresight Exercises

Skulimowski

2021

Progress in IS

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The results of recent foresight projects reveal the impact of future ICT tools on the practice of scientific research. This paper presents several aspects of the process of building scenarios and trends of selected advanced ICT technologies. We point out the implications of emerging global expert systems (GESs) and AI-based learning platforms (AILPs). GESs will be capable of using and processing global knowledge from all available sources, such as databases, repositories, video streams, interactions with other researchers and knowledge processing units. In many scientific disciplines, the high volume, density and increasing level of interconnection of data have already exhausted the capacities of any individual researcher. Three trends may dominate the development of scientific methodology. Collective research is one possible coping strategy: Group intellectual capacity makes it possible to tackle complex problems. Recent data flow forecasts indicate that even in the few areas, which still resist ICT domination, research based on data gathered in non-ICT supported collections will soon reach its performance limits due to the ever-growing amount of knowledge to be acquired, verified, exchanged and communicated between researchers. Growing automation of research is the second option: Automated expert systems will be capable of selecting and processing knowledge to the level of a professionally edited scientific paper, with only minor human involvement. The third trend is intensive development and deployment of brain–computer interfaces (BCIs) to quickly access and process data. Specifically, GESs and AILPs can be used together with BCIs. The above approaches may eventually merge, forming a few AI-related technological scenarios, as discussed to conclude the paper.

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AI Alignment of Disaster Resilience Management Support Systems

Skulimowski

Bañuls

2021

Artificial Intelligence and Soft Computing

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Forward-Looking Activities Supporting Technological Planning of AI-Based Learning Platforms

Cited by 6 publications

References 13 publications

A future‐oriented approach to the selection of artificial intelligence technologies for knowledge platforms

A future‐oriented approach to the selection of artificial intelligence technologies for knowledge platforms

Visions of a Future Research Workplace Arising from Recent Foresight Exercises

AI Alignment of Disaster Resilience Management Support Systems

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