Interactive Qualitative Data Visualization for Educational Assessment

Nguyen, Huyen; Trujillo, Caleb; Wee, Kevin; Bowe, Kathleen A.

doi:10.1145/3468784.3469851

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…An individual student's learning route is "adapted" in real-time by adaptive learning software using AI or machine learning techniques. There are various strategies to increase students' knowledge intake and retention, which is the cornerstone of learning [61], [62]. For instance, AI in education has removed national and international borders, allowing global access to learning through online and webbased platforms [63], [64].…”

Section: Ai Based Learning Approachmentioning

confidence: 99%

Artificial intelligent based teaching and learning approaches: A comprehensive review

Nguyen,

Tran

2023

IJERE

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<span lang="EN-US">The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates.</span>

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Section: Ai Based Learning Approachmentioning

confidence: 99%

Artificial intelligent based teaching and learning approaches: A comprehensive review

Nguyen,

Tran

2023

IJERE

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“…Our approach aligns with this direction, but we shift the focus on the analysis side with different malware families and the influence of operating systems on malware behavior. In particular, the design decisions and techniques in MalView are applied in the malware analysis domain and derived from visualization principles for time-series data, which is the collection of observations through repeated measurements over time, including but not limited to numerical, geolocation, and text data [73]- [75]. Using Ether [61] as the monitoring platform, Quist and Liebrock [76] propose a directed graph structure of all the basic blocks of an executable with a navigable interface to explore the code structure.…”

Section: Visualization Tools and Analysismentioning

confidence: 99%

MalView: Interactive Visual Analytics for Comprehending Malware Behavior

et al. 2022

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Malicious applications are usually comprehended through two major techniques, namely static and dynamic analyses. Through static analysis, a given malicious program is parsed, and some representative artifacts (e.g., control-flow graphs) are produced without any execution; whereas, the given malicious application needs to be executed when conducting dynamic analysis. These two mainstream techniques for analyzing the given software are effective in detecting certain classes of malware. More specifically, through static analysis, the patterns and signature of the malware are exposed, helping in detecting any known malicious payload hidden in or injected into the code. On the other hand, behavioral and run-time execution patterns of software are explored through dynamic analysis. To ease the analysis process, a third analysis approach, known as the visual representation of the artifacts created by both static and dynamic analysis tools, would also be a supplementary asset for malware experts. This paper introduces "MalView", an interactive visualization platform, for malware analysis by which pattern matching techniques on both signature-based and behavioral analysis artifacts can be utilized to 1) classify malware, 2) identify the intention and location of the malicious payload in the artifacts, 3) analyze unknown malware (i.e., zero-day malware) by recognizing any unusual signature or behavior, and 4) explore the time dependencies and thus the system components affected or tampered by the underlying malware. The results of several case studies conducted in this work show that MalView offers more features and information compared to some other visualization tools, facilitating the malware analysis process.INDEX TERMS Malware analysis, dynamic analysis, malware visualization system, visual analytics.

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Qualitative Research Challenges in Assessing Rainwater Harvesting Implementation Fidelity for Reliable Data

Mohd Latif,

Mohamed,

Donyavi

et al. 2024

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Assessing local councils’ adherence to rainwater harvesting policy regulated in the by-laws is critical to the success of water conservation efforts. However, there are certain challenges that must be addressed in this assessment. This paper highlights the aforementioned challenges and provides recommendations for future research. The research used a qualitative approach, employing six distinct methods to obtain more robust and reliable data: (i) desk study, (ii) document review, (iii) interviews, (iv) observation, (v) self-analysis questions and (vi) focus group discussion. The success of the implementation-focused research was based on a defined direction of assessment, eligible participants and sites, suitable methods, access to reliable data, robust analysis and writing proficiency. This paper suggests that future search should focus on establishing relevant skills, building relationships with the participants, defining concepts and exploring alternative data sources. Assessing implementation fidelity was not easy because it necessitated substantial resources to draw meaningful conclusions about the extent to which the rainwater harvesting policy was delivered. Addressing qualitative research challenges in assessing rainwater harvesting implementation could enable researchers to suggest implementers on making more informed decisions in attaining Sustainable Development Goal 6.

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Interactive Qualitative Data Visualization for Educational Assessment

Cited by 3 publications

References 20 publications

Artificial intelligent based teaching and learning approaches: A comprehensive review

Artificial intelligent based teaching and learning approaches: A comprehensive review

MalView: Interactive Visual Analytics for Comprehending Malware Behavior

Qualitative Research Challenges in Assessing Rainwater Harvesting Implementation Fidelity for Reliable Data

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