Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic

The research is about emotion recognition and analysis based on Micro-blog short text. Emotion recognition is an important field of text classification in Natural Language Processing. The data of this research comes from Micro-blog 100K record related to COVID-19 theme collected by Data fountain platform, the data are manually labeled, and the emotional tendencies of the text are negative, positive and neutral. The empirical part adopts dictionary emotion recognition method and machine learning emotion recognition respectively. The algorithms used include support vector machine and naive Bayes based on TFIDF, support vector machine and LSTM based on wod2vec. The five results are compared. Combined with statistical analysis methods, the emotions of netizens in the early stage of the epidemic are analyzed for public opinion. This research uses machine learning algorithm combined with statistical analysis to analyze current events in real time. It will be of great significance for the introduction and implementation of national policies

Conceive design implement operate approach for a lab module

The Conceive-Design-Implement-Operate has been globally recognized as an enabler for engineering education reformation. With the CDIO process, the CDIO Standards and the CDIO Syllabus, many scholarly contributions have been made in curriculum reform and learning environments. Therefore, CDIO approach recognizes that the engineering education can be acquired from a variety of institutions and the educators in all parts of this spectrum can learn the CDIO practice elsewhere. Thus, the purpose of this study is to use the CDIO approach for an Engineering Mathematics Lab Module. For Concieve stage, three different pre-tests were conducted to identify the difficult course outcome in Engineering Mathematics for the students. A total of eight course outcomes are identified as the most difficult course outcomes in Engineering Mathematics subjects. In the design stage, an innovative lab module was developed based on the difficult course outcomes from the conceive stage. The lab module was designed in analytical and using Mathematica software. The Engineering Mathematics Lab Module was implement to Electrical Engineering department students. In the operation stage, the response from the students were obtained for the Engineering Mathematics Lab Module. Generally students’ performance were improved in Engineering Mathematics using CDIO approach

Evaluating students performance in advanced programming final exam questions

Students grade in a subject is determine mainly from the final examination marks. The final exam questions need to be reliable in order to measure the performance of students in the particular subject. Rasch model able to measure the reliability of an instrument, the final exam questions. A total of 60 students from the School of Information Technology sat for the Advanced Programming final examination. Marks were entered in excel and transferred as *prn format. Marks were analyzed against the Rasch model, WINSTEPS. The summary statistics for person, summary statistics for item, item dimensionality, item statistics, item distribution map and person distribution map  are among the output being analyzed. Two items were identified as misfit items. The Advanced Programming exam questios was very reliable and able to give insight view of the questions. A corrective action is taken to review the misfit item and rephrase the item

EVALUATING THE RELIABILITY OF PRE-TEST DIFFERENTIAL EQUATIONS QUESTIONS USING RASCH MEASUREMENT MODEL

A good exam questions should be able to gauge student’s understanding and achievement related to Course Outcome (CO), Bloom’s Taxonomy level and Programme Outcome (PO). To achieve this, a set of pre-test questions were prepared to evaluate the pre achievement level among the students related to CO, PO and the Bloom’s Taxonomy level. In this study, a pre-test for Differential Equations (KKKQ2123) was given to 100 second year students from the department of Electrical, Electronic and Systems Engineering. The level of Bloom’s Taxonomy measured consists of level 1 (knowledge) to level 6 (creation). Rasch Measurement Model was applied to analyse the reliability of the pre-test questions. The analysis revealed that all the pre-test questions were reliable and no questions were found unsuitable. Prior assessment (pre-test) is important in the preparation of final exam questions as it would indicate the level of student’s understanding in a particular topic that relates to the CO and PO of the programme

Evaluating performance of students in engineering statistics final exam questions

Engineering Statistics is one of Engineering Mathematics subject which is common for all the engineering courses besides Vector Calculus, Linear Algebra, Differential Equations and Numerical Analysis. Students performance in Engineering Statistics subject can be evaluated examining through the final exam questions. Students need to understand the concept learn through a semester or 14 weeks of period and do necessary preparation to do the final exam questions. Rasch model is used to evaluate students performance in Engineering Statistics examination. A total of 114 engineering students sat for Engineering Statistics final examination. There are 5 Course Outcomes and 2 Programme Outcomes for Engineering Statistics subject. The final exam marks were entered in excel. Then the marks transferred to *prn format. Next Rasch model generate the output. The outputs are summary statistics  for person, summary statistics for item, item map and person map. The summary statistics for person able to groups the students into 2 groups, namely high performers and low performers. On the other hand, the items can be group into 4 groups. They are difficult, mediocre, easy and very easy. The item map and the person map able to show those groups clearl

Evaluation of pilot test on improving students’ performance using rasch model

Poor performance of students in Engineering Mathematics can be overcome by introducing innovative way in teaching. Teaching Engineering Mathematics via lab has been proven to boost the students’ performance in Engineering Mathematics. Thus, the objective of this study is to conduct a pilot test to evaluate students’ knowledge prior to introducing lab session to engineering undergraduates. A pilot test was conducted on third semester students in engineering faculty. A total of 35 students from Electrical Engineering, Civil Engineering and Chemical Engineering participated in the pilot test. Six course outcomes are chosen from Vector Calculus, Linear Algebra and Ordinary Differential Equations subjects. Six subjective questions were prepared and the questions were validated by three internal experts. The results of the test were analyzed against Rasch model. The item reliability 0.69 shows an average difficulty of spread of the pilot test questions. Furthermore, the summary statistics for item shows the questions can be separated into two different groups. The person-item distribution map shows that the distribution of questions categorized into difficult and easy groups. Question1 and question 2 fall into easy group. Question 3, question 4 and question 5 and question 6 fall into difficult group

Achievement of course outcome in vector calculus pre-test questions

No AbstractKeywords: pre-test; course outcome; bloom taxanomy; Rasch measurement model; vector calculu

Evaluating reliability of final exam questions via rasch model

Students grade in a subject is determine mainly from the final examination marks. The final exam questions need to be reliable in order to measure the performance of students in the particular subject. Rasch model able to measure the reliability of an instrument, the final exam questions. A total of 114 students from Mechanical Engineering department sat for the Engineering Statistics subject. Marks were entered in excel and transferred as *prn format. Marks were analyzed against Rasch model, WINSTEPS. The summary statistics for person, summary statistics for item, item statistics, item dimensionality and item correlation are among the output being analyzed. One item is identified as misfit item. The Engineering Sattistics exam questios was very reliable and able to give insight view of the questions. A corrective action is taken to review the misfit item and rephrase the item

Analysis on numerical analysis final exam questions

Numerical Analysis is one of the key topics for Computational Mathematics in Engineering Mathematics. Students required to learn different methods of analysis to solve a given problem. The objective of this paper is to analyze the final exam questions of Numerical Analysis subject. There are four course outcomes for the Numerical Analysis subject. Five questions were set up for final and each question carries 20 marks. The Bloom Taxonomy for the questions are from application and analysis level. A total of 32 students from Civil Engineering department took the final examination. To analyze this subject, the results of the final examination of students from Civil Engineering department are tabulated in EXCEL and transformed into WINSTEPS. The Rasch model enables one to differentiate the difficulties of the exam questions according to different levels of the group. The ability of the Civil Engineering students cannot be divided into any group. A misfit item identified from Point-Measure Correlation, Outfit MNSQ and Outfit z-Standard. Since no item is out of the three measures, therefore there is no misfit question for the Numerical Analysis final examination. The person-item distribution map showed the questions which belong to difficult, easy and very easy group