Distributed Systems

2018


  1. Analytical tool for the modelling and simulation of curriculum: Towards automated design, assessment, and improvement (), In International Journal of Engineering Education, volume 35, .

    Abstract

    © 2019 TEMPUS Publications. Continuous quality improvement cycle is essential in educational systems allowing institutions to meet the evolving needs of the market. As such, it is required by all accreditation agencies. Curriculum revision is a critical step of this cycle. This study proposes a modelling paradigm to automate the design, analysis and improvement of curriculum. Based on proven theoretical principles, this novel graph-based approach captures both pre-requisite and cognitive dependencies among courses, enabling an optimal learning environment for students. The presented tool allows an easy and fast analysis of the impact of potential course revisions on all other courses, hence enabling a better continuous quality improvement process, thus providing benefits to many stakeholders in the education system, namely managers, instructors, students and employers. The proposed modelling paradigm is explained and illustrated on a capstone project course offered in the College of Computer Science and IT.


    Keywords: Accreditation, Automated tool, Curriculum design, Curriculum development, Engineering education, Quality assurance


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  2. Fostering higher cognitive skills through design thinking in digital hardware course: A case study (, and ), In ICIC Express Letters, volume 13, .

    Abstract

    © 2019 ICIC International. All rights reserved. Computer Science students are reportedly facing many issues in acquiring higher cognitive skills (e.g., analysis, and design). Digital hardware is one of the first courses in a typical Computer Science curriculum where students need to master these skills while analyzing and designing sequential circuits. This study investigates the pedagogical effectiveness of the Design Thinking methodology in improving students' higherorder cognitive skills in the digital hardware course. Design Thinking was embedded in the digital hardware course through a real-world design challenge where teams of students iteratively collaborated. The design problem was purposely set to necessitate knowledge and skills yet to be covered hence fostering in students' curiosity and eagerness to learn new topics, thus engaging students as active learners and meaning creators. The study demonstrates a significant gain in test scores. It also describes how to easily embed the Design Thinking process in the digital hardware curriculum.


    Keywords: Analysis, Continuous quality improvement, Design, Design Thinking, Digital Logic, Higherorder cognitive skills, Student learning outcomes


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  3. The u-can-act Platform: A Tool to Study Intra-individual Processes of Early School Leaving and Its Prevention Using Multiple Informants (, , , , and ), In Frontiers in Psychology, volume 10, .

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  4. Energy management for user's thermal and power needs: A survey ( and ), In Energy Reports, volume 5, .

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  5. IMOS: improved meta-aligner and Minimap2 on spark (, and ), In BMC bioinformatics, Springer, volume 20, .

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  6. Variability in business processes: Automatically obtaining a generic specification (, , and ), In Information Systems, volume 80, .

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  7. Office Multi-Occupancy Detection using BLE Beacons and Power Meters (, and ), In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics, and Mobile Communication Conference, .

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  8. Temporal Analysis of 911 Emergency Calls Through Time Series Modeling (, , and ), In The International Conference on Advances in Emerging Trends and Technologies, .

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  9. Prediction of Imports of Household Appliances in Ecuador Using LSTM Networks (, , and ), In Conference on Information Technologies and Communication of Ecuador, .

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  10. Predictive CO2-Efficient Scheduling of Hybrid Electric and Thermal Loads ( and ), In 2019 IEEE International Conference on Energy Internet (ICEI), .

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  11. ECiDA: Evolutionary Changes in Data Analysis (, , , , , , , and ), In ICT.Open, Hilversum, The Netherlands, .

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  12. Development of a decision-aid for patients with depression considering treatment options: prediction of treatment response using a data-driven approach (, , , , , , , , , and ), In ISPOR Europe 2019, Copenhagen, Denmark, .

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  13. Time to get personal? The impact of researchers’ choices on the selection of treatment targets using the experience sampling methodology (, , , , , , , , , and ), PsyArXiv, .

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