Learning pattern classification using moodle logs and the visualization of browsing processes by time-series cross-section

Dobashi, Konomu; Ho, Curtis; Fulford, Catherine P.; Lin, Meng-Fen Grace; Higa, Christina

doi:10.1016/j.caeai.2022.100105

Cited by 13 publications

(6 citation statements)

References 48 publications

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“…Subsequent process discovery [25] facilitated the explication of the distinct characteristics inherent to each learning pattern, which span a spectrum from rigid conformity to prescribed educational sequences to a more autonomous and adaptive learning stance. Such heterogeneity in learning modalities not only encapsulates the multifaceted dimensions of the learning process [43,44] but also substantiates the efficacy of our investigative framework in encapsulating the nuanced dynamics of learner-material interaction [45].…”

Section: Discussion For Resultssupporting

confidence: 60%

Integrating Business Analytics in Educational Decision-Making: A Multifaceted Approach to Enhance Learning Outcomes in EFL Contexts

Cho,

Kim,

Kim

et al. 2024

Mathematics

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This study introduces a framework that integrates business analytics into educational decision-making to improve learner engagement and performance in Massive Open Online Courses (MOOCs), focusing on learning environments in English as a Foreign Language (EFL). By examining three specific research questions, this paper delineates patterns in learner engagement, evaluates factors that affect these patterns, and examines the relationship between these factors and educational outcomes. The study provides an empirical analysis that elucidates the connection between learner behaviors and learning outcomes by employing machine learning, process mining, and statistical methods such as hierarchical clustering, process discovery, and the Mann–Kendall test. The analysis determines that learning patterns, characterized as single-phase or multi-phase, repetitive or non-repetitive, and sequential or self-regulated, are more closely associated with the nature of the educational content—such as books, series, or reading levels—than learner characteristics. Furthermore, it has been observed that learners exhibiting self-regulated learning patterns tend to achieve superior academic outcomes. The findings advocate for integrating analytics in educational practices, offer strategic insights for educational enhancements, and propose a new perspective on the connection between learner behavior and educational success.

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Section: Discussion For Resultssupporting

confidence: 60%

Integrating Business Analytics in Educational Decision-Making: A Multifaceted Approach to Enhance Learning Outcomes in EFL Contexts

Cho,

Kim,

Kim

et al. 2024

Mathematics

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“…Secondly, it has a deviation normalized to use constant logistic function parameters (to keep an outer logistic function input in a range of (0-2). From Equation (16), it is necessary to mention that logistic functions may have different parameters, for example, {b, x 0 }, also according to Equation (15). For example, we denote parameters b = 5, x 0 = 0.9 in order to create the logistic curve, as is depicted in Figure 4.…”

Section: Logistic Functionmentioning

confidence: 99%

“…Focus Approach Limitations [12] Anomaly detection in time-series data Focused on the unsupervised environment and taxonomy for outlier detection Not inclined toward patternless [13] Rare pattern discovery in time-series Using repeated sub-sequences in time-series Does not show utilities for wide-range real-life dataset [14,15] Real-time patternless IDS Non-signature based/patternless IDS for thermodynamics hardly focused on a time series approach [16] Learning patterns over time-series Pattern classifications using logs and processes over time-series…”

Section: Refmentioning

confidence: 99%

“…To highlight the contribution of this paper, the authors have explored the state-of-theart studies, as depicted in [6,[12][13][14][15][16][17][18][19][20][21][22], which have shown relevant similarities and differences where necessary, which in the context of this study has provided concrete insights that have enabled the authors of this paper to concentrate on the main problems/contributions of NP-AD in Time-Series.…”

Section: Introductionmentioning

confidence: 99%

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Non-Pattern-Based Anomaly Detection in Time-Series

et al. 2023

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Anomaly detection across critical infrastructures is not only a key step towards detecting threats but also gives early warnings of the likelihood of potential cyber-attacks, faults, or infrastructure failures. Owing to the heterogeneity and complexity of the cybersecurity field, several anomaly detection algorithms have been suggested in the recent past based on the literature; however, there still exists little or no research that points or focuses on Non-Pattern Anomaly Detection (NP-AD) in Time-Series at the time of writing this paper. Most of the existing anomaly detection approaches refer to the initial profiling, i.e., defining which behavior represented by time series is “normal”, whereas everything that does not meet the criteria of “normality” is set as “abnormal” or anomalous. Such a definition does not reflect the complexity and sophistication of anomaly nature. Under different conditions, the same behavior may or may not be anomalous. Therefore, the authors of this paper posit the need for NP-AD in Time-Series as a step toward showing the relevance of deviating or not conforming to expected behaviors. Non-Pattern (NP), in the context of this paper, illustrates non-conforming patterns or a technique of deviating with respect to some characteristics while dynamically adapting to changes. Based on the experiments that have been conducted in this paper, it has been observed that the likelihood of NP-AD in Time-Series is a significant approach based on the margins of data streams that have been used from the perspective of non-seasonal time series with outliers, the Numenta Anomaly Benchmark (NAB) dataset and the SIEM SPLUNK machine learning toolkit. It is the authors’ opinion that this approach provides a significant step toward predicting futuristic anomalies across diverse cyber, critical infrastructures, and other complex settings.

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“…Akan tetapi untuk menunjang kemudahan hal tersebut manual book ataupun pelatihan penggunaan moodle perlu menjadi perhatian selanjutnya. Hal ini senada dengan yang disampaikan Carol dan Puspasari [23] serta Dobashi Dkk [24] bahwa moodle merupakan e-learning interaktif yang mudah digunakan karena dapat membuat peserta didik berinteraksi dengan pendidik menjadi lebih menyenangkan menggunakan fitur untuk media pembelajaran seperti Video, Kuis, e-book, bahkan penggunaan log ataupun aktifitas yang dilaksanakan agar bisa diklasifikasikan pada pola pembelajaran masing-masing siswa.…”

Section: Kemudahan Proses Pembelajaran Dengan Moodleunclassified

Evaluasi Penerapan Moodle Dalam Pembelajaran Kejuruan Menggunakan Gibb's Reflective Learning Cycle

Affandi¹,

Lestari²

2022

JOIVE

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<p>Good interaction between educators and learners can encourage the achievement of learning objectives. However, if the interaction goes well, the result will be the opposite. Moreover, the learning process needs to encourage students to think critically. However, it will instead become a burden in the learning process so that there is no collaboration between students during the learning process. This study aims to understand the perceptions of teachers and students towards the application of the Moodle Learning Management System (LMS) to improve learning outcomes that are still low using several types of learning media. This research uses a qualitative approach with Gibb's Reflective Learning Cycle technique to obtain the perceptions of educators and students. This research was conducted because, in the learning process, many still need to learn to use technology appropriately. The media used is less innovative and limited, so learning has yet to be created that encourages students to think critically and comprehensively. Unlike moodle research in general, this research is used to evaluate two sides of using technology, especially moodle, in helping the learning process, namely on the side of educators and students. </p>

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Learning pattern classification using moodle logs and the visualization of browsing processes by time-series cross-section

Cited by 13 publications

References 48 publications

Integrating Business Analytics in Educational Decision-Making: A Multifaceted Approach to Enhance Learning Outcomes in EFL Contexts

Integrating Business Analytics in Educational Decision-Making: A Multifaceted Approach to Enhance Learning Outcomes in EFL Contexts

Non-Pattern-Based Anomaly Detection in Time-Series

Evaluasi Penerapan Moodle Dalam Pembelajaran Kejuruan Menggunakan Gibb's Reflective Learning Cycle

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