A Personality-Driven Recommender System for Cross-Domain Learning Based on Holland Code Assessments

Over the past few decades, AI has been widely used in the field of education. However, very little attention has been paid to the use of AI for enhancing the quality of cross-domain learning. College/university students are often interested in different domains of knowledge but may be unaware of how to choose relevant cross-domain courses. Therefore, this paper presents a personality-driven recommender system that suggests cross-domain courses and related jobs by computing personality similarities and probable course grades. In this study, 710 students from 12 departments in a Taiwanese university conducted Holland code assessments. Based on the assessments, a comprehensive empirical study, including objective and subjective evaluations, was performed. The results reveal that (1) the recommender system shows very promising performances in predicting course grades (objective evaluations), (2) most of the student testers had encountered difficulties in selecting cross-domain courses and needed the further support of a recommender system, and (3) most of the student testers positively rated the proposed system (subjective evaluations). In summary, Holland code assessments are useful for connecting personalities, interests and learning styles, and the proposed system provides helpful information that supports good decision-making when choosing cross-domain courses.

Investigation into the Negative Factors in English Vocabulary Acquisition of College Students

Vocabulary acquisition is the premise of learning language. In English learning, college students always feel perplexed and painful on acquiring English vocabulary. Therefore, this paper aims to analyze and reveal negative factors in English vocabulary acquisition of college students and put forward some countermeasures. Compared with previous studies, this paper comprehensively analyzes most of negative factors on English vocabulary acquisition and according to collected data, more concrete and practical measures are put forward to help college students acquire English vocabulary. Interviews and questionnaires are conducted in turn. Interviews with college students and teachers shows there are many factors that have an negative impact on vocabulary acquisition such as the influence of Chinese and culture, individual motivation, learning habits and teaching model. Questionnaire shows the difficulties and learning habits most students had as well as English teaching model they desire. Through questionnaire, it is found that low motivation is the most influential factor and there is a relationship between students’ grade and their motivation. At the end of this paper, some countermeasures are proposed to help students learn vocabulary more effectively.

Student Collaborative Learning Strategies

The authors of this study utilized the logistic regression analysis using extreme student groups (top and bottom quartiles) defined by students' collaborative learning scores to develop a model for predicting group membership of low and high levels of collaborative learning college students. The focus of the study was to identify characteristics of the learning environment that differentiate between high and low collaborative learning groups. Results of the logistic regression showed a statistically significant model that can be used to reliably predict student's classification into low or high collaborative learning groups based on the selected institution and personal variables. The logistic regression model showed the lowest total percent correctly classified was at 98.1% while the highest total percent correctly classified was at 98.6%. Majority of the model variables made significant differences between the low and high collaborative learning groups. ANOVA results indicate significant group differences in all the predictor variables.

The Role Of College Students In Achieving Sustainable Development Goals Post - Pandemic Covid – 19

The study examines the roles of college students in advancing sustainable development goals after covid-19.Questionnaire and interviews were employed.The research was carried out on college students across some continents through online interviews.Descriptive statistics that include frequency distribution and mean were used to analyze all data collected from both ends. From the result of the research,it was discovered that to enhance sustainable development goals,the health of an individual should be paramount.A threat to citizens health constitutes an immense challenge in achieving sustainable development goals. College students should adhere strictly to rules of personal hygiene,adequate nutrition,regular exercise and adequate rest.Also they should encourage and sensitize their peers,family members and the society at large on the importance of healthy living. Students should employ conventional methods of learning and engage in practical activities,vocational education should also be encouraged. Agricultural students should work more on site in commercial methods in order to produce large quantities of foods that will sustain society rather than a more theoretical approach of learning. College students should involve in voluntary community development activities and sensitize the community on how to maintain the available infrastructure in the society.Also, factors such as child-parent interaction,students-Teachers interaction, Intellectual and emotional development should be promoted by the students. College students should be aware of the harmful effects of climate change and environmental pollution.They should be aware of the need to reduce energy consumption in lighting ,cooking and transportation by using energy saving light bulbs,turning on the light only when necessary,use devices that work with solar energy,use public transport,bicycle and / or travel on foot.There is a need for union between different religion in order to promote peace and to achieve sustainable development goals.

Implementasi Algoritma TOPSIS dan Metode EUCS untuk Pengujian Sistem Penilaian Kinerja Pegawai pada Laboran Fakultas Teknologi Informasi UKSW Salatiga

<p>Pegawai laboratorium merupakan tenaga kerja kependidikan yang membantu proses pembelajaran mahasiswa dalam bagian vokasi dan akademik. Dalam menjalankan pekerjaannya, pegawai laboratorium terkadang masih belum maksimal. Sehingga kepala sarana &amp; prasarana dan supervisor harus mengontrol pegawai untuk memastikan pegawai berkerja dengan baik. Untuk mengatasi permasalahan dalam pegawai laboratorium serta membantu dalam memanajemen kinerja, dibuatlah sistem informasi berbasis <em>website</em> yang berisi implementasi algoritma TOPSIS pada penilaian kinerja pegawai laboratorium. Terdapat enam kriteria penilaian pegawai laboratorium yang terdiri dari kedisiplinan, tanggung jawab, kerja tim, <em>skill</em>, akademik, dan komunikasi. Hasil akhir penelitian berupa nilai preferensi (Vi) setiap alternatif, dimana terdapat nilai preferensi tertinggi yaitu 1 yang diperoleh 3 dari 12 orang pegawai pada pengujian algoritma TOPSIS. Penyajian sistem informasi dilakukan dengan <em>database</em> yang ditampilkan menggunakan desain <em>dashboard</em> yang tepat digunakan untuk manajemen data. Pengujian EUCS pada <em>website </em>sistem informasi adalah 3.41 dari total nilai kepuasan (4) yang tergolong dalam kategori puas, sehingga dianggap layak dan diterima oleh <em>user</em>. </p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>Laboratory employee is a education labor which help process learning college student within part of vocational and academic. In carrying out his work, laboratory employee sometimes it's still not optimal. So that the head of facilities &amp; infrastructure and supervisor must control the employee to make sure employees are working well. For counter the problem in laboratory employee and help in performance management, made information system based on website which contain implementation of the TOPSIS algorithm on performance rating of the laboratory employee. There are six laboratory employee rating criteria which consisting of dicipline, responsible, team work, skill, academic, and communication. Last result of the research is the form of preference values (Vi) every alternatif, where there is highest preference value is 1 which is obtained 3 out of 12 employee of the TOPSIS algorithm testing. Presentment of the information system perform with database and displayed using dashboard design which exact used for present data management. EUCS testing on information system website is 3.41 from total</em> <em>satisfaction value (4) which classified of satisfied categori, so that good considered and accepting by user.</em></p>

Analyzing the Students’ Behavior Characteristics of Learning College English Vocabulary

The paper is aimed for three tasks: to review why learning vocabulary matters, what’s in a word and what knowing a word means, to demonstrate the students’ behavior characteristics of learning vocabulary through the result analysis of a questionnaire survey and interviews and to provide enlightenment about the future teaching and learning of college English.