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Steps towards a philosophy of computing education. [Discussion paper]. (2024)
Conference Proceeding
MCDERMOTT, R., DANIELS, M. and FREZZA, S.T. 2024. Steps towards a philosophy of computer education. [Discussion paper]. In Mühling, A. and Jormanainen, I. (eds.) Proceedings of the 23rd Koli calling international conference on computing education research 2023, 13-18 November 2024, Koli, Finland. New York: ACM [online], article 20. Available from: https://doi.org/10.1145/3631802.3631817

Is it meaningful to talk about the philosophy of computing education? What is its subject matter and methods? Is it different from, or a subfield of, the philosophy of science education or the philosophy of technology education or the philosophy of e... Read More about Steps towards a philosophy of computing education. [Discussion paper]..

Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19. (2023)
Conference Proceeding
JOHNSTON, P., ZARB, M. and MORENO-GARCIA, C.F. 2023. Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023),18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article number 10343048. Available from: https://doi.org/10.1109/fie58773.2023.10343048

This paper presents an experience report of online attendance and associated behavioural patterns during a module in the first complete semester undertaken fully online in the autumn of 2020, and the corresponding module deliveries in 2021 and 2022.... Read More about Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19..

Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK. (2023)
Conference Proceeding
LINTILÄ, T. 2023. Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK. In Chova, L.G., Martínez. C.G. and Lees, J. (eds.) Proceedings of the 15th International conference on education and new learning technologies (EDULEARN 2023), 3-5 July 2023, Palma, Spain. Valencia: IATED [online], pages 2121-2129. Available from: https://doi.org/10.21125/edulearn.2023.0638

This article describes research in which the Learning by Developing (LbD) action model has been used as a teaching and learning method for computer science students in Finland and Great Britain. The study has been conducted as action research, and it... Read More about Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK..

A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs. (2023)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2023. A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs. In Chova, L.G., Martínez. C.G. and Lees, J. (eds.) Proceedings of the 17th International technology, education and development conference (INTED 2023), 6-8 March 2023, Valencia, Spain. Valencia: IATED [online], pages 3261-3269. Available from: https://doi.org/10.21125/inted.2023.0897

This article describes a study in which the Learning by Developing (LbD) action model has been used as a teaching and learning method for computing students in Finland and the United Kingdom. The study has been carried out as action research, and the... Read More about A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs..

What is Skill? (and why does it matter?). (2023)
Conference Proceeding
MCDERMOTT, R. and DANIELS, M. 2023. What is skill? (and why does it matter?). In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343520. Available from: https://doi.org/10.1109/FIE58773.2023.10343520

This Research-to-Practice Full Paper seeks to investigate the concept of Skill within a Competency Framework, such as that described by the CC2020 document. The notion of skill is fundamental to modern educational discourse. As educators, we strive,... Read More about What is Skill? (and why does it matter?)..

Evaluating a pass/fail grading model in first year undergraduate computing. (2023)
Conference Proceeding
ZARB, M., MCDERMOTT, R., MARTIN, K., YOUNG, T. and MCGOWAN, J. 2023. Evaluating a pass/fail grading model in first year undergraduate computing. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343276. Available from: https://doi.org/10.1109/FIE58773.2023.10343276

This Innovative Practice Full Paper investigates the implications of implementing a Pass/Fail marking scheme within the undergraduate curriculum, specifically across first year computing modules in a Scottish Higher Education Institution. The motivat... Read More about Evaluating a pass/fail grading model in first year undergraduate computing..

In search of a philosophy of computing education. (2023)
Conference Proceeding
MCDERMOTT, R., DANIELS,M. and FREZZA, S. 2023. In search of a philosophy of computing eduction. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343513. Available from: https://doi.org/10.1109/FIE58773.2023.10343513

In this paper, we present a preliminary description of the field of inquiry encompassed by the philosophy of computing education. We first attempt to identify a general framework for investigating characteristic questions of a philosophical nature th... Read More about In search of a philosophy of computing education..

A weighted ensemble of regression methods for gross error identification problem. (2023)
Conference Proceeding
DOBOS, D., DANG, T., NGUYEN, T.T., MCCALL, J., WILSON, A., CORBETT, H. and STOCKTON, P. 2023. A weighted ensemble of regression methods for gross error identification problem. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Symposium series on computational intelligence (SSCI 2023), 5-8 December 2023, Mexico City, Mexico. Piscataway: IEEE [online], pages 413-420. Available from: https://doi.org/10.1109/SSCI52147.2023.10371882

In this study, we proposed a new ensemble method to predict the magnitude of gross errors (GEs) on measurement data obtained from the hydrocarbon and stream processing industries. Our proposed model consists of an ensemble of regressors (EoR) obtaine... Read More about A weighted ensemble of regression methods for gross error identification problem..

MicroConceptBERT: concept-relation based document information extraction framework. (2023)
Conference Proceeding
SILVA, K., SILVA, T. and NANAYAKKARA, G. 2023. MicroConceptBERT: concept-relation based document information extraction framework. In Proceedings of the 7th SLAAI (Sri Lanka Association for Artificial Intelligence) International conference on artificial intelligence 2023 (SLAAI-ICAI 2023), 23-24 November 2023, Kelaniya, Sri Lanka. Piscataway: IEEE [online], article number 10365022. Available from: https://doi.org/10.1109...ICAI59257.2023.10365022

Extracting information from documents is a crucial task in natural language processing research. Existing information extraction methodologies often focus on specific domains, such as medicine, education or finance, and are limited by language constr... Read More about MicroConceptBERT: concept-relation based document information extraction framework..

SecHealth: enhancing EHR security in digital health transformation. (2023)
Conference Proceeding
YENG, P., FAUZI, M.A., YANG, B., DIEKUU, J.-B., NIMBE, P., HOLIK, F., KHATIWADA, P., FAHMI, A. and SUN, L. 2023. SecHealth: enhancing EHR security in digital health transformation. In Widasari, E.R. and Adikara, P.P. (eds.) SIET '23: proceedings of the 8th International conference on sustainable information engineering and technology (SIET '23), 24-25 October 2023, Bali, Indonesia. New York: ACM [online], pages 538-544. Available from: https://doi.org/10.1145/3626641.3627214

In the contemporary wave of digital transformation, the implementation of electronic health records (EHRs) has become a pivotal undertaking for numerous nations. However, amidst this technological advancement, a critical facet deserving heightened at... Read More about SecHealth: enhancing EHR security in digital health transformation..

On the role of dialogue models in the age of large language models. (2023)
Conference Proceeding
WELLS, S. and SNAITH, M. 2023. On the role of dialogue models in the age of large language models. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) Computational models of natural argument 2023: proceedings of the 23rd Computational models of natural argument workshop 2023 (CMNA 2023), 3 December 2023, [virtual conference]. CEUR workshop proceedings, 3614. Aachen: CEUR-WS [online], pages 49-51. Available from: https://ceur-ws.org/Vol-3614/abstract2.pdf

We argue that Machine learning, in particular the currently prevalent generation of Large Language Models (LLMs), can work constructively with existing normative models of dialogue as exemplified by dialogue games, specifically their computational ap... Read More about On the role of dialogue models in the age of large language models..

Explaining a staff rostering problem by mining trajectory variance structures. (2023)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W., CHRISTIE, L.A., ZĂVOIANU, A.-C., BROWNLEE, A.E.I. and AINSLIE, R. 2023. Explaining a staff rostering problem by mining trajectory variance structures. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI international conference on artificial intelligence (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 275-290. Available from: https://doi.org/10.1007/978-3-031-47994-6_27

The use of Artificial Intelligence-driven solutions in domains involving end-user interaction and cooperation has been continually growing. This has also lead to an increasing need to communicate crucial information to end-users about algorithm behav... Read More about Explaining a staff rostering problem by mining trajectory variance structures..

Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement. (2023)
Conference Proceeding
COLLINS, J., ZĂVOIANU, A.-C. and MCCALL, J.A.W. 2023. Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI (Specialist Group on Artificial Intelligence) Artificial intelligence international conference 2023 (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 451-464. Available from: https://doi.org/10.1007/978-3-031-47994-6_39

Rosters are often used for real-world staff scheduling requirements. Multiple design factors such as demand variability, shift type placement, annual leave requirements, staff well-being and the placement of trainees need to be considered when constr... Read More about Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement..

Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. (2023)
Conference Proceeding
MEKALA, M.S., EYAD, E. and SRIVASTAVA, G. 2023. Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. In Proceedings of the 10th IEEE (Institute of Electrical and Electronics Engineers) Data science and advanced analytics international conference 2023 (DSAA 2023), 9-13 October 2023, Thessaloniki, Greece. Piscataway: IEEE [online], 10302554. Available from: https://doi.org/10.1109/DSAA60987.2023.10302554

Sharing up-to-date information about the surrounding measured by On-Board Units (OBUs) and Roadside Units (RSUs) is crucial in accomplishing traffic efficiency and pedestrians safety towards Intelligent Transportation Systems (ITS). Transferring meas... Read More about Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems..

Siamese residual neural network for musical shape evaluation in piano performance assessment. (2023)
Conference Proceeding
LI, X., WEISS, S., YAN, Y., LI, Y., REN, J., SORAGHAN, J. and GONG, M. 2023. Siamese residual neural network for musical shape evaluation in piano performance assessment. In Proceedings of the 31st European signal processing conference 2023 (EUSIPCO 2023), 4-8 September 2023, Helsinki, Finland. Piscataway: IEEE [online], pages 216-220. Available from: https://doi.org/10.23919/EUSIPCO58844.2023.10289901

Understanding and identifying musical shape plays an important role in music education and performance assessment. To simplify the otherwise time- and cost-intensive musical shape evaluation, in this paper we explore how artificial intelligence (AI)... Read More about Siamese residual neural network for musical shape evaluation in piano performance assessment..

Detecting contradictory COVID-19 drug efficacy claims from biomedical literature. (2023)
Conference Proceeding
SOSA, D.N., SURESH, M., POTTS, C. and ALTMAN, R.B. 2023. Detecting contradictory COVID-19 drug efficacy claims from biomedical literature. In Rogers, A., Boyd-Graber, J. and Okazaki, N. (eds.) Proceedings of the 61st Association for Computational Linguistics annual meeting 2023 (ACL 2023), 9-14 July 2023, Toronto, Candada. Stroudsburg, PA: ACL [online], volume 2: short papers, pages 694-713. Available from: https://doi.org/10.18653/v1/2023.acl-short.61

The COVID-19 pandemic created a deluge of questionable and contradictory scientific claims about drug efficacy – an "infodemic" with lasting consequences for science and society. In this work, we argue that NLP models can help domain experts distill... Read More about Detecting contradictory COVID-19 drug efficacy claims from biomedical literature..

Towards feasible counterfactual explanations: a taxonomy guided template-based NLG method. (2023)
Conference Proceeding
SALIMI, P., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2023. Towards feasible counterfactual explanations: a taxonomy guided template-based NLG method. In Gal, K., Nowé, A., Nalepa, G.J., Fairstein, R. and Rădulescu, R. (eds.) ECAI 2023: proceedings of the 26th European conference on artificial intelligence (ECAI 2023), 30 September - 4 October 2023, Kraków, Poland. Frontiers in artificial intelligence and applications, 372. Amsterdam: IOS Press [online], pages 2057-2064. Available from: https://doi.org/10.3233/FAIA230499

Counterfactual Explanations (cf-XAI) describe the smallest changes in feature values necessary to change an outcome from one class to another. However, many cf-XAI methods neglect the feasibility of those changes. In this paper, we introduce a novel... Read More about Towards feasible counterfactual explanations: a taxonomy guided template-based NLG method..

Gated recurrent unit autoencoder for fault detection in penicillin fermentation process. (2023)
Conference Proceeding
PETROVSKI, A., ARIFEEN, M. and PETROVSKI, S. 2023. Gated recurrent unit autoencoder for fault detection in penicillin fermentation process. In Kovalev, S., Kotenko, I. and Sukhanov, A. (eds.) Proceedings of the 7th Intelligent information technologies for industry international scientific conference 2023 (IITI'23), 20-25 September 2023, St. Petersburg, Russia, volume 1. Lecture notes in networks and systems (LNNS), 776. Cham: Springer [online], pages 86-95. Available from: https://doi.org/10.1007/978-3-031-43789-2_8

The penicillin fermentation process is a fed-batch system to generate industrial-scale penicillin for antibiotic production. Any fault in the fermentation tank can lead to low-quality penicillin products, which may cause a severe impact on final anti... Read More about Gated recurrent unit autoencoder for fault detection in penicillin fermentation process..

Unmasking the imposters: task-specific feature learning for face presentation attack detection. (2023)
Conference Proceeding
ABDULLAKUTTY, F., ELYAN, E. and JOHNSTON, P. 2023. Unmasking the imposters: task-specific feature learning for face presentation attack detection. In Proceedings of the 2023 International joint conference on neural networks (IJCNN2023), 18-23 June 2023, Gold Coast, Australia. Piscataway: IEEE [online], 10191953. Available from: https://doi.org/10.1109/IJCNN54540.2023.10191953

Presentation attacks pose a threat to the reliability of face recognition systems. A photograph, a video, or a mask representing an authorised user can be used to circumvent the face recognition system. Recent research has demonstrated high accuracy... Read More about Unmasking the imposters: task-specific feature learning for face presentation attack detection..

CBR driven interactive explainable AI. (2023)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., MARTIN, K., CORSAR, D., NKISI-ORJI, I., PALIHAWADANA, C., BRIDGE, D., PRADEEP, P., AGUDO, B.D. and CARO-MARTÍNEZ, M. 2023. CBR driven interactive explainable AI. In MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023, (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages169-184. Available from: https://doi.org/10.1007/978-3-031-40177-0_11

Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Numerous explanation techniques (explainers) exist in the literature, and recent findings suggest that addressing multiple user needs requi... Read More about CBR driven interactive explainable AI..