Process Modeling, Behavior Analytics and Group Performance Assessment of e-Learning Logs Via Fuzzy Miner Algorithm

Premchaiswadi, Wichian; Porouhan, Parham; Premchaiswadi, Nucharee

doi:10.1109/compsac.2018.10247

Cited by 9 publications

(10 citation statements)

References 14 publications

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“…McCall & Kölling, 2019; Ullah et al, 2019;Ureel & Wallace, 2019;Albluwi, 2018;Bhatia, Kohli & Singh, 2018;Lagus et al, 2018;Lin et al, 2018;Turner, Pérez-Quiñones & Edwards, 2018;Wainer & Xavier, 2018;Castro-Wunsch, Ahadi & Petersen, 2017;Ahadi, Hellas & Lister, 2017;Echeverría et al, 2017;Hsiao, Huang & Murphy, 2017;Malliarakis, Satratzemi & Xinogalos, 2016;Scott et al, 2015;Xinogalos, 2015;Allinjawi, Al-Nuaim & Krause, 2014;Omer, Farooq & Abid, 2020 Greater or equal to 4 and less than 5 18Azcona, Hsiao & Smeaton, 2018;Esteero et al, 2018;Gomes & Correia, 2018;King, 2018;Koong et al, 2018;Premchaiswadi, Porouhan & Premchaiswadi, 2018;Dorodchi, Dehbozorgi & Frevert, 2017;España-Boquera et al, 2017;Estey, Keuning & Coady, 2017;Fu et al, 2017;Kumar, 2017;Seanosky et al, 2017;Seeling & Eickholt, 2017;Gomes, Correia & Abreu, 2016;Seeling, 2016;Simkins & Decker, 2016;Ahadi et al, 2015;Ashenafi, Riccardi & Ronchetti, 2015;Carter, Hundhausen & Adesope, 2015;Hilton & Rague, 2015;Janke, Br...…”

Section: Year-wise Publication Trendsmentioning

confidence: 99%

“…A framework was proposed for detailed examination of students' understanding of various concepts to identify the troublesome concepts (Yeomans, Zschaler & Coate, 2019). The time spent on performing various course related activities has been observed as a commonly utilized parameter to analyze learning in framework-based research (Chaweewan et al, 2018;Premchaiswadi, Porouhan & Premchaiswadi, 2018). The case studies were conducted, e.g., to check the effect of altering the content sequence (Janke, Brune & Wagner, 2015) and to identify the impact of teaching different programming languages on learning (Santana, Figueredo & Bittencourt, 2018).…”

Section: Year-wise Publication Trendsmentioning

confidence: 99%

“…Studies, in this category, examined the relationship between students' interaction with tools and their performance in exams. In this context, the features that were evaluated include the number of actions performed, access time, and the frequency of using one or more sections of tools (Premchaiswadi, Porouhan & Premchaiswadi, 2018;Ahadi, Hellas & Lister, 2017). Moreover, the changes in the compilation states were also considered to determine the students' performance (Carter, Hundhausen & Adesope, 2015;Carter, Hundhausen & Adesope, 2017).…”

Section: Xinogalos 2015mentioning

confidence: 99%

“…McCall & Kölling, 2019;Azcona, Hsiao & Smeaton, 2018;Pereira et al, 2020;Chaweewan et al, 2018;Omer, Farooq & Abid, 2020;Ninrutsirikun et al, 2020;Premchaiswadi, Porouhan & Premchaiswadi, 2018;Turner, Pérez-Quiñones & Edwards, 2018;Ahadi, Hellas & Lister, 2017;Ahmad et al, 2017;al-Rifaie, Yee-King & d'Inverno, 2017;Carter, Hundhausen & Adesope, 2017;Castro-Wunsch, Ahadi & Petersen, 2017;Chung & Hsiao, 2020;Funabiki, Ishihara & Kao, 2016;Watson, Li & Godwin, 2014;Ahadi et al, 2015;Ashenafi, Riccardi & Ronchetti, 2015;Carter, Hundhausen & Adesope, 2015 Approach examination Liao et al, 2019;King, 2018;Lagus et al, 2018;Lin et al, 2018;Santana, Figueredo & Bittencourt, 2018;Effenberger, Pelánek & Čechák, 2020;Echeverría et al, 2017;España-Boquera et al, 2017;Iqbal Malik & Coldwell-Neilson, 2017;Seeling & Eickholt, 2017;Malliarakis, Satratzemi & Xinogalos, 2016;Seeling, 2016;Hilton & Rague, 2015;Janke, Brune & Wagner, 2015;Rubio et al, 2014;Rosiene & Rosiene, 2015;Scott et al, 2015;Wood & Keen, 2015;…”

Section: Features Inspectionmentioning

confidence: 99%

See 3 more Smart Citations

Introductory programming course: review and future implications

Omer

Farooq

Abid

2021

PeerJ Computer Science

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The introductory programming course (IPC) holds a special significance in computing disciplines as this course serves as a prerequisite for studying the higher level courses. Students generally face difficulties during their initial stages of learning how to program. Continuous efforts are being made to examine this course for identifying potential improvements. This article presents the review of the state-of-the-art research exploring various components of IPC by examining sixty-six articles published between 2014 and 2020 in well-reputed research venues. The results reveal that several useful methods have been proposed to support teaching and learning in IPC. Moreover, the research in IPC presented useful ways to conduct assessments, and also demonstrated different techniques to examine improvements in the IPC contents. In addition, a variety of tools are evaluated to support the related course processes. Apart from the aforementioned facets, this research explores other interesting dimensions of IPC, such as collaborative learning, cognitive assessments, and performance predictions. In addition to reviewing the recent advancements in IPC, this study proposes a new taxonomy of IPC research dimensions. Furthermore, based on the successful practices that are listed in the literature, some useful guidelines and advices for instructors have also been reported in this article. Lastly, this review presents some pertinent open research issues to highlight the future dimensions for IPC researchers.

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Section: Year-wise Publication Trendsmentioning

confidence: 99%

Section: Year-wise Publication Trendsmentioning

confidence: 99%

Section: Xinogalos 2015mentioning

confidence: 99%

Section: Features Inspectionmentioning

confidence: 99%

See 2 more Smart Citations

Introductory programming course: review and future implications

Omer

Farooq

Abid

2021

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…This model is based on 0.5 utilization ratio, which means this model considers significance and correlation equally. The use of fuzzy miner features aggregation and abstraction [5], [25], where it enables the analyst to highlight particular subset of activities. Aggregation is used for clustering coherent, less significant structures.…”

Section: Process Discovery Using Original Fuzzy Minermentioning

confidence: 99%

Improved fuzzy miner algorithm for business process discovery

2021

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Return material authorization (RMA) is a process in which a company decides to repair or replace customer's defect product during the warranty period. To execute RMA, both company and customer obliged to follow standard operating procedure (SOP) which usually consists of many business processes of a company well. As the business process could cause inefficiencies, a company should improve their business process regularly. The best way is using process discovery. This research proposes a new improved fuzzy miner algorithm to represent binary correlation between activities. This new algorithm utilizes binary significance and binary correlation equally to acquire fuzzy model. While the original fuzzy miner algorithm uses various binary correlation metrics, the improved fuzzy miner algorithm uses only one metric and could capture the fuzzy model, accurately based on the event logs to capture more accurate business process model. In this research, ProM fuzzy miner is used as a comparison to the proposed improved time-based fuzzy miner. The results showed that the improved algorithm has higher value on conformance checking and able to capture business process model based on time interval, by using only time-interval significance as a binary correlation metrics.

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