Impact of Practical Skills on Academic Performance: A Data-Driven Analysis

Rahman, Md. Mostafizer; Watanobe, Yutaka; Kiran, R. Uday; Thang, Truong Cong; Paik, Incheon

doi:10.1109/access.2021.3119145

Cited by 29 publications

(14 citation statements)

References 46 publications

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“…A unique approach for evaluating the impact of practical knowledge on educational accomplishments was indicated by M. M. Rahman et al, in their study [12]. A remarkable approach for retrieving latent features and corresponding association rules from a legitimate dataset is presented in this research.…”

Section: Prior Research and Novelty Of Teamentioning

confidence: 88%

Integrated Assessment of Teaching Efficacy: A Natural Language Processing Approach

Chandrapati¹,

Rao²

2023

IJACSA

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The most significant component in the education domain is evaluation. Apart from student evaluation, teacher evaluation plays a vital role in the colleges or universities. The implementation of a scientific and appropriate assessment method for enhancing teaching standards in educational institutions is absolutely essential. Conventional teacher assessment techniques have always been bounded to bias and injustice for single dimensional assessment criteria, biased scoring, and ineffective integration. In this regard,it is crucial to develop a specialized teacher evaluation assistant (TEA) system that integrates with some computational intelligence algorithms. This research concentrates on using Natural language processing(NLP) based techniques for empirically analysing teaching effectiveness. We develop a model in which a teacher is evaluated based on the content he delivers during a lecture. Two techniques are employed to evaluate teacher effectiveness using topic modelling and text clustering. By the application of topic modelling, an accuracy of 75% is achieved and text clustering achieved an accuracy of 80%. Thus, the method can effectively be deployed to assess and predict the effectiveness of a teacher's teaching.

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Section: Prior Research and Novelty Of Teamentioning

confidence: 88%

Integrated Assessment of Teaching Efficacy: A Natural Language Processing Approach

Chandrapati¹,

Rao²

2023

IJACSA

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“…The MK-means clustering algorithm contains two (02) new modules: (i) an initial center selection module (ICSM) to select the optimal centers, and (ii) an outlier detection module (ODM) to identify and remove irrelevant data points from the dataset. The MK-means algorithm has been applied to a variety of data analysis and applications [24], [29]. The pseudocodes of these two modules ICSM and ODM of the MK-means clustering algorithm are shown in Algorithm 1 and Algorithm 2, respectively.…”

Section: A Elbow and Mk-means Clustering Algorithmmentioning

confidence: 99%

“…In [23], the performance of clustering algorithms is automatically compared and the most efficient clustering algorithm is recommended based on the dataset. Statistical data analysis is performed on programming logs and test scores to investigate the hidden information of programmers in the study [24]. Furthermore, EDM can be employed to find useful knowledge and information from problem-solving data to support programming learning.…”

Section: Introductionmentioning

confidence: 99%

Educational Data Mining to Support Programming Learning Using Problem-Solving Data

et al. 2022

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Computer programming has attracted a lot of attention in the development of information and communication technologies in the real world. Meeting the growing demand for highly skilled programmers in the ICT industry is one of the major challenges. In this point, online judge (OJ) systems enhance programming learning and practice opportunities in addition to classroom-based learning. Consequently, OJ systems have created a large number of problem-solving data (solution codes, logs, and scores) archives that can be valuable raw materials for programming education research. In this paper, we propose an educational data mining framework to support programming learning using unsupervised algorithms. The framework includes the following sequence of steps: (i) problem-solving data collection (logs and scores are collected from the OJ) and preprocessing; (ii) MK-means clustering algorithm is used for data clustering in Euclidean space; (iii) statistical features are extracted from each cluster; (iv) frequent pattern (FP)-growth algorithm is applied to each cluster to mine data patterns and association rules; (v) a set of suggestions are provided on the basis of the extracted features, data patterns, and rules. Different parameters are adjusted to achieve the best results for clustering and association rule mining algorithms. For the experiment, approximately 70,000 realworld problem-solving data from 537 students of a programming course (Algorithm and Data Structures) were used. In addition, synthetic data have leveraged for experiments to demonstrate the performance of MK-means algorithm. The experimental results show that the proposed framework effectively extracts useful features, patterns, and rules from problem-solving data. Moreover, these extracted features, patterns, and rules highlight the weaknesses and the scope of possible improvements in programming learning.

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“…From the perspective of cognitive psychology, researchers believe that teaching ability combines general ability and special ability [13][14][15]. General ability refers to the four abilities of teaching design, teaching implementation and regulation, evaluation and reflection, and teaching research; special ability refers to the cognition of teaching and comprehension, experimental skills, and inquiry skills [16,17].…”

Section: Related Workmentioning

confidence: 99%

English Teaching Ability Evaluation Algorithm Based on Random Matrix Model and Fuzzy K-Means Clustering

Shen

2022

Mathematical Problems in Engineering

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This paper proposes a nonelliptic extended English teaching ability evaluation algorithm based on an adaptive random matrix model. The algorithm models a nonelliptical expansion target as multiple elliptical sub-objectives, and the expansion state of each sub-target is described by an inverse Wishart distribution. The new method is combined to improve the robustness problem caused by the initialization after the algorithm expansion. This research uses the smart teacher education platform to conduct research and analysis on the evaluation of teaching practice ability of intern normal students. From the perspective of data evaluation, we explore the influence of normal students’ curriculum training on the teaching practice ability of normal students. By analyzing the correlation between normal students’ course grades and practice grades, this paper explores the influence of normal students’ prepractice training on normal students’ teaching practice ability. This paper explores the influence of the training of normal students’ course learning on the teaching practice ability of normal students. The results show that the learning level of normal students’ professional courses has a significant impact on the development of normal students’ practice performance and teaching practice ability; the impact of normal students’ pedagogical course level on normal students’ practice performance and teaching practice ability is relatively low.

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Impact of Practical Skills on Academic Performance: A Data-Driven Analysis

Cited by 29 publications

References 46 publications

Integrated Assessment of Teaching Efficacy: A Natural Language Processing Approach

Integrated Assessment of Teaching Efficacy: A Natural Language Processing Approach

Educational Data Mining to Support Programming Learning Using Problem-Solving Data

English Teaching Ability Evaluation Algorithm Based on Random Matrix Model and Fuzzy K-Means Clustering

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