Analyzing Teaching Performance of Instructors Using Data Mining Techniques

Mardikyan, Sona; Badur, Bertan

doi:10.15388/infedu.2011.17

Cited by 38 publications

(8 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In addition to its efficiency and accuracy in evaluating potential predictor variables ( Collins, 2021 ), the CHAID analysis also provides a Risk estimate that specifies the proportion of cases classified incorrectly ( Mardikyan and Badur, 2011 ). In our study, the relatively elevated Risk estimate may indicate that these patterns of pedagogical actions are flexible.…”

Section: Discussionmentioning

confidence: 99%

Preschool teachers display a flexible pattern of pedagogical actions in promoting healthy habits in children

2023

View full text Add to dashboard Cite

The school represents the optimal setting for promoting the physical, emotional, and social health of children, especially during the first years of life. Understanding the pedagogical actions of teachers to address health education is an important first step in promoting healthy behaviors in children. We inhere analyzed the pedagogical action patterns in the preschool teaching of healthy habits from a holistic health perspective. We used photography as a strategy for data collection and applied a Chi-square automatic interaction detection (CHAID) classification tree, a data mining procedure, to generate a pattern model. We found that the school space and the learning playfulness strategies for the development of executive functions, classified according to the exercise, symbolic, assembly, rules (ESAR) model, were the main factors that influence the pedagogical actions fostering healthy habits. By contrast, the school and the pedagogical resources of the classroom are factors with a much smaller impact on working with healthy habits. This pedagogical action pattern is flexible, since teachers conduct a multiplicity of pedagogical actions through different strategies, in different school spaces, at any time. In conclusion, our results unmask the interdependent relationships between the different factors that determine the teacher’s actions at the preschool. It also contributes to the understanding of the teacher’s practices in fostering healthy habits in a healthy learning environment.

show abstract

Section: Discussionmentioning

confidence: 99%

Preschool teachers display a flexible pattern of pedagogical actions in promoting healthy habits in children

2023

View full text Add to dashboard Cite

show abstract

“…They use a total of 223 respondents who were recruited using multistage sampling. The results showed that the lecturer and tutor characteristics, subject characteristics, the studentship and learning resources and facilities were positively correlated with overall lecturer performance at a significant level(p<=0.5) (17) .…”

Section: Related Workmentioning

confidence: 92%

“…Mardikyan and Badur (17) conducted a study to understand the key factors affecting the teaching performance of the instructors through regression and Decision Tree algorithms. The data were collected anonymously from students' evaluation records to identify the factors associated with the teaching performance of instructors, and variables related to instructor and course characteristics.…”

Section: Related Workmentioning

confidence: 99%

Data mining techniques for classifying and predicting Teachers’ performance based on their evaluation reports

Salem¹

2021

IJST

View full text Add to dashboard Cite

Background/Objectives: Teachers' performance is a key bridge to ensure successful pedagogical and educational objectives. However, the evaluation of teachers' performance has been used to be a manual and temperamental task for school principals. This traditional context limits the teachers' engagement to develop his/her performance as well as the principle to predict the strengths and weaknesses attached. Hence, schools' principals need to use initiative methods to evaluate the teachers' performance. In this study, a comparative approach was developed to evaluate the teachers' performance aiming at avoiding the potential biased and temperamental human behaves in the teacher's evaluation process. Methods: It involves different Data Mining (DM) techniques to identify the key patterns that are driving the teachers' performance evaluation process. Therefore, the proposed approach extracts several potential and influential indicators mined from a paper-based on teachers' performance reports at the Directorate of Education/ Southern Ghawrs, along with some demographics variables. Several DM algorithms are used to analyze teachers' performance reports and predict their performance, such as NB Tree, Naïve Bayes, and Conjunctive Rule methods. Findings: The experimental results show a significant prediction accuracy improvement by (33%) when applying NB Tree compared to Conjunctive rule, and (12%) when compared to Naïve Bayes techniques respectively.

show abstract

“…In [13], linear regression is used to model the amount of accumulated knowledge. In [14], using step-by-step regression and decision tree from data mining techniques, the factors that affect the teaching performance of professors in the university are identi ed and the results show that the attitude of the instructor, the status of the teacher, the presence of students, and the feedback of students. It affects teaching performance.…”

Section: Introductionmentioning

confidence: 99%

Recommender System for Predicting the Academic Status of Students of Bangladesh Using Artificial Neural network

Shirzad

2023

Preprint

View full text Add to dashboard Cite

Today, information technology in different areas produces a large amount of data every day. In recent years, many researchers have started to extract knowledge from data to make data-based decisions and improve the quality of processes in various organizations. Educational data mining helps educational institutions to operate effectively and efficiently by leveraging data from all stakeholders. It can help students at risk; create recommendation systems and alert students at different levels. Recently, neural network has received much attention in the educational sector compared to other methods. In this article, a study has been done using neural network on the dataset of Bangladesh University. The evaluation criteria for performance comparison are MAE (mean absolute error) and MSE (mean square error). The MAE and MSE of the neural network in the first run are 0.1357 and 0.026123, respectively. With the neural network, a recommender system has been presented to predict the students' academic status, which considers the student's status in four states: "excellent", "good", "needs more effort" and "needs guidance".

show abstract

Analyzing Teaching Performance of Instructors Using Data Mining Techniques

Cited by 38 publications

References 19 publications

Preschool teachers display a flexible pattern of pedagogical actions in promoting healthy habits in children

Preschool teachers display a flexible pattern of pedagogical actions in promoting healthy habits in children

Data mining techniques for classifying and predicting Teachers’ performance based on their evaluation reports

Recommender System for Predicting the Academic Status of Students of Bangladesh Using Artificial Neural network

Contact Info

Product

Resources

About