Course Evaluation Based on Deep Learning and SSA Hyperparameters Optimization

Sentiment analysis attracts the attention of Egyptian Decisionmakers in the education sector.It offers a viable method to assess education quality services based on the students’feedback as well as that provides an understanding of their needs.As machine learning techniques offer automated strategies to process big data derived from social media and other digital channels,this research uses a dataset for tweets’sentiments to assess a few machine learning techniques.After dataset preprocessing to remove symbols,necessary stemming and lemmatization is performed for features extraction.This is followed by several machine learning techniques and a proposed Long Short-Term Memory(LSTM)classifier optimized by the Salp Swarm Algorithm(SSA)and measured the corresponding performance.Then,the validity and accuracy of commonly used classifiers,such as Support Vector Machine,Logistic Regression Classifier,and Naive Bayes classifier,were reviewed.Moreover,LSTM based on the SSA classification model was compared with Support Vector Machine(SVM),Logistic Regression(LR),and Naive Bayes(NB).Finally,as LSTM based SSA achieved the highest accuracy,it was applied to predict the sentiments of students’feedback and evaluate their association with the course outcome evaluations for education quality purposes.

Using the RUFDATA Framework to Devise a Plan for a Course Evaluation

This paper aims to devising an evaluation plan for an Integrated English Course within the RUFDATA framework in an attempt to illuminate the working mechanism of the Framework.

Research and Practice on the Multi-dimensional Course Goal Achievement Evaluation of Software Engineering

According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.

Research on the Assessment System of Computational Mechanics Courses Based on the TOPSIS Entropy Weight Model

This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.

Scale for Evaluation of Humanities Courses: Development, Reliability and Validity

The present paper deals with development of a course evaluation survey (CES) questionnaire regarding evaluation of humanities courses (e.g., Commerce/Economics/Law) and assessment of its validity and reliability. Taking help from available questionnaires and also incorporating views from the teachers of the related subjects, the relevant Likert type items were selected. The drafted version of the questionnaire was finalized taking into account feedback from the subject experts. The focus was on simple language to ensure clarity to the students to facilitate accuracy of the collected data. The developed questionnaire consists of five domains involving fifteen Likert type items including a global item. For assessment of its reliability and validity, data were collected among two groups of undergraduate students studying two courses namely Accounts (n = 190) and Law (n = 90). For assessing questionnaire, Karl Pearson Correlation Coefficient, Cronbach’s Alpha coefficient and four factor solutions under factor analysis were used. The analytical results were quite consistent across the data sets (that are, accounts, law and pooled together) that exhibit good psychometric properties. It may thus be concluded that the questionnaire is valid, reliable and may measure what it is intended to measure.

Thinking and Practice on the Construction of Innovative Practice Course

Innovative practice courses are the basis for the implementation of innovation credit and play an important role in cultivating college students'innovative ability.Innovative practice courses should be based on guiding innovation.The construction of courses needs to be carried out comprehensively in the aspects of course content,class organization,and course evaluation methods.Based on the construction of innovative practice courses"Mobile Development Technology Practice",the attempt in the construction of innovative practice courses is introduced.There are still some problems in the development of innovative practice courses in the course selection,evaluation,time setting,and the improvement of innovation,which is needed to be resolved in many ways.In response to the problems,some thoughts and suggestions is given in the paper.