Academic literature on the topic 'Teachers Prediction of occupational success Academic achievement'

Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students’ academic achievement early using Educational Data Mining (EDM). This study aims to predict students’ final grades and identify honorary students at an early stage. Background: EDM research has emerged as an exciting research area, which can unfold valuable knowledge from educational databases for many purposes, such as identifying the dropouts and students who need special attention and discovering honorary students for allocating scholarships. Methodology: In this work, we have collected 300 undergraduate students’ records from three departments of a Computer and Information Science College at a university located in Saudi Arabia. We compared the performance of six data mining methods in predicting academic achievement. Those methods are C4.5, Simple CART, LADTree, Naïve Bayes, Bayes Net with ADTree, and Random Forest. Contribution: We tested the significance of correlation attribute predictors using four different methods. We found 9 out of 18 proposed features with a significant correlation for predicting students’ academic achievement after their 4th semester. Those features are student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses, i.e., database fundamentals, programming language (1), and computer network fundamentals. Findings: The empirical results show the following: (i) the main features that can predict students’ academic achievement are the student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses; (ii) Naïve Bayes classifier performed better than Tree-based Models in predicting students’ academic achievement in general, however, Random Forest outperformed Naïve Bayes in predicting honorary students; (iii) English language skills do not play an essential role in students’ success at the college of Computer and Information Sciences; and (iv) studying an orientation year does not contribute to students’ success. Recommendations for Practitioners: We would recommend instructors to consider using EDM in predicting students’ academic achievement and benefit from that in customizing students’ learning experience based on their different needs. Recommendation for Researchers: We would highly endorse that researchers apply more EDM studies across various universities and compare between them. For example, future research could investigate the effects of offering tutoring sessions for students who fail core courses in their first semesters, examine the role of language skills in social science programs, and examine the role of the orientation year in other programs. Impact on Society: The prediction of academic performance can help both teachers and students in many ways. It also enables the early discovery of honorary students. Thus, well-deserved opportunities can be offered; for example, scholarships, internships, and workshops. It can also help identify students who require special attention to take an appropriate intervention at the earliest stage possible. Moreover, instructors can be aware of each student’s capability and customize the teaching tasks based on students’ needs. Future Research: For future work, the experiment can be repeated with a larger dataset. It could also be extended with more distinctive attributes to reach more accurate results that are useful for improving the students’ learning outcomes. Moreover, experiments could be done using other data mining algorithms to get a broader approach and more valuable and accurate outputs.

The aim of this study was to reveal whether the success orientation, self-handicapping behaviours and demographic features of the classroom teachers predict their school alienation in a meaningful way of or not. This research is a descriptive study that has the relational screening model which aims at determining the success orientation, self-handicapping behaviours and demographic features of the classroom teachers, which affect their school alienation levels, and identifying their mutual interaction.The population of the study consisted of 370 students of Çukurova University Faculty of Education, Department of Primary School Teaching, in the educational year 2014-2015. The data were collected by means of Students Alienation Scale developed by Çağlar (2012), 2X2 Success Orientation Scale of which validity and reliability tests were performed by Akın (2006a), Translation into Turkish by Özgüngör (2008), Preemptive Behavior scale of which validity and reliability tests were performed and Personal Information Form prepared by the researcher. The data obtained were analysed using the SPSS 21.0 programme. Correlation analysis was made in order to reveal relations among the variables. Multiple regression analysis was used in order to identify the variables that predict the school alienation levels of the students of primary school teaching.As a result of the multiple regression analysis that were made, it has been understood that powerlessness sub-dimension of school alienation by students of primary school teaching predicts respectively learning-approach, poor relations with the teaching stuff, learning-avoidance, self-handicapping and very low academic success level; the normlesness sub-dimension predicts learning-approach, academic success grade, performance-approach, learning-avoidance, poor relations with the teaching stuff; the isolation sub-dimension predicts very good relations with classmates, performance-approach, learning-avoidance, medium level relations with classmates and choosing department; the meaninglessness sub-dimension predicts performance-avoidance, learning-avoidance, self-handicapping, choosing department, poor relations with the teaching stuff and the gender; total point of school alienation learning- approach, self-handicapping, choosing department, poor relations with the teaching stuff, acedemic success grade, performance-avoidance, learning- avoidance, variables. ÖzetBu araştırmanın amacı, sınıf öğretmenliği öğrencilerinin başarı yönelimi, kendini engelleme davranışları ve demografik özelliklerinin okula yabancılaşmalarını anlamlı bir şekilde yordayıp yordamadığını ortaya çıkartmaktır. Araştırma, sınıf öğretmenliği öğrencilerinin okula yabancılaşma düzeylerini etkileyen başarı yönelimleri, kendini engelleme davranışları ve demografik özelliklerinin saptanması ve bunların birbirleriyle etkileşimlerinin belirlenmesini amaçlayan ilişkisel tarama modelinde betimsel bir çalışmadır.Araştırmanın evrenini 2014-2015 eğitim-öğretim yılında Çukurova Üniversitesi Eğitim Fakültesi Sınıf Öğretmenliği Bölümünde öğrenim gören 370 öğrenci oluşturmaktadır. Araştırmanın verileri Çağlar (2012) tarafından geliştirilen Öğrenci Yabancılaşma Ölçeği, Akın (2006a) tarafından geçerlik güvenirlik çalışması yapılan 2X2 Başarı Yönelimleri Ölçeği, Özgüngör (2008) tarafından Türkçeye çevrisi, geçerliği ve güvenirlik çalışması yapılan Engelleyici Davranış ölçeği ve araştırmacı tarafından hazırlanan Kişisel Bilgi Formu ile toplanmıştır. Elde edilen veriler SPSS 21.0 programında çözümlenmiştir. Değişkenler arası ilişkilerin ortaya çıkarılması amacıyla korelâsyon analizi yapılmıştır.Sınıf öğretmenliği öğrencilerinin okula yabancılaşma düzeylerini yordayıcı değişkenlerin ortaya çıkarılması için çoklu regresyon analizi kullanılmıştır.Yapılan çoklu regresyon analizleri sonucunda sınıf öğretmenliği öğrencilerinin okula yabancılaşmanın Güçsüzlük alt boyutunu sırasıyla, öğrenme-yaklaşma, öğretim elemanları ile zayıf ilişkiler, öğrenme-kaçınma, kendini engelleme ve çok düşük akademik başarı düzeyi; Kuralsızlık alt boyutunu, öğrenme-yaklaşma, akademik başarı notu, performans-yaklaşma, öğrenme- kaçınma, öğretim elemanlarıyla zayıf ilişki; Soyutlanma alt boyutunu, sınıf arkadaşlarıyla çok iyi düzeyde ilişki, performans-yaklaşma, sınıf arkadaşlarıyla orta düzeyde ilişki ve bölümü seçme ; Anlamsızlık alt boyutunu, performans-kaçınma, öğrenme-kaçınma, kendini engelleme, bölüm seçme, öğretim elemanlarıyla zayıf ilişki ve cinsiyet, Okula yabancılaşma toplam puanını, öğrenme-yaklaşma, kendini engelleme, bölüm seçme, öğretim elemanları ile zayıf ilişkiler, akademik başarı notu, performans-kaçınma, öğrenme-kaçınma değişkenlerinin yordadıkları anlaşılmıştır.

Abstract The tremendous growth of educational institutions’ electronic data provides the opportunity to extract information that can be used to predict students’ overall success, predict students’ dropout rate, evaluate the performance of teachers and instructors, improve the learning material according to students’ needs, and much more. This paper aims to review the latest trends in predicting students’ performance in higher education. We provide a comprehensive background for understanding Educational Data Mining (EDM). We also explain the measures of determining academic success and highlight the strengths and weaknesses of the most common data mining (DM) tools and methods used nowadays. Moreover, we provide a rich literature review of the EDM work that has been published during the past 12 years (2007–2018) with focus on the prediction of academic performance in higher education. We analyze the most commonly used features and methods in predicting academic achievement, and highlight the benefits of the mostly used DM tools in EDM. The results of this paper could assist researchers and educational planners who are attempting to carry out EDM solutions in the domain of higher education as we highlight the type of features that the previous researches found to have significant impact on the prediction, as well as the benefits and drawbacks of the DM methods and tools used for predicting academic outcomes.

Abstract This paper reports the findings of a case study that attempted to identify school-related factors influencing the quality of implementation of the Tier 1 Program of the Project P.A.T.H.S. in Hong Kong. The case study method was utilized to investigate perceptions of the program implementers of program effectiveness, and to identify the crucial factors for program success in a school with a religious background that admits students with high academic achievement. Findings demonstrated that incorporation of the program into the formal curriculum, good administrative support, efficient management from school, and presence of dedicated teachers contributed to program success. The present findings provide insight for the implementation of the Project P.A.T.H.S. in schools with a religious background.

In their efforts to make the selection and hiring process more efficient, school administrators utilize teacher selection instruments such as the Web-based TeacherInsight™ assessment tool (The Gallup Organization, Princeton, NJ). Tools such as these instruments are now used regularly by school systems across the nation to assess teachers regarding their knowledge, talents, skills, attitudes, and values. According to Gallup, the TeacherInsight is a predictor of teacher talent and is based on 12 themes. This study utilized 132 elementary and secondary teachers and approximately 4,500 students currently enrolled in Grades 3 through 11 to determine if the TeacherInsight is a predictor of student achievement. This study considered: (1) the relationship between the TeacherInsight and student achievement as measured by the Texas Growth Index (TGI); (2) the relationship between teacher characteristics (years of experience, level [primary or secondary], gender, age, degree) and the TeacherInsight instrument; (3) the relationship between teacher characteristics (years of experience, level [primary or secondary], gender, age, degree) and student achievement as measured by the TGI; and (4) the relationship between student classifications (limited English proficient, economically disadvantaged, at-risk) and student achievement as measured by the TGI. The analyses found a very weak positive relationship between the TeacherInsight and student achievement using the TGI in the subjects of English/ reading and math. Additional analysis based on levels (primary and secondary) between TeacherInsight scores and TGI values were not significant. Teacher characteristics were poor predictors of scores on the TeacherInsight. Of the characteristics, years of teaching experience was the strongest predictor of scores on the TeacherInsight. Although the overall analyses indicated significant relationships, they were very weak for both English/reading and math. Teacher characteristics were also poor predictors of student achievement. Again, the overall analysis indicated a significant but weak relationship for both English/reading and math. When considering the relationship between student classifications of LEP, economically disadvantaged, and at-risk, only at-risk had a weak relationship to student achievement. The findings provide little support to the validity of TeacherInsight in terms of its ability to predict student achievement scores and its usefulness as a tool for the selection of teachers by school systems. Until more extensive research is completed on the TeacherInsight and its impact on student achievement, no definitive answers for school systems can be made. Suggestions and recommendations for future studies are provided in the discussion section.

This ex post facto study sought to examine: the efficacy of Mosby's Assess Test as a valid predictor of NCLEX (National Council of State Boards of Nursing Licensure Examination) scores; significant correlations among semester averages, semester tests failed, Nelson Denny Reading Test scores, and NCLEX scores; and differences in NCLEX outcomes in relation to ethnicity, age, and prior practical nursing licensure for 558 associate degree nursing graduates who wrote the NCLEX in 1983 and 1984. Significant positive relationships were found among Mosby scores, Nelson Denny scores, semester averages, and NCLEX scores. A significant negative relationship was found between number of semester tests failed and NCLEX scores. The mean NCLEX score of older graduates was higher than the mean NCLEX score of younger graduates. LPN graduates had a higher mean NCLEX score than non-LPN graduates. White graduates' mean NCLEX score was greater than the average score for black graduates. Combined predictor variables which yielded the best estimate of the criterion variable (NCLEX scores) for all graduates included mean semester average, Mosby scores, age above thirty-three, and Nelson Denny scores, respectively. The most important predictor of black graduates' NCLEX success was prior practical nursing licensure. Other significant predictors for black graduates' NCLEX success were mean semester average, Mosby scores, mean number of semester tests failed, age above thirty-three, and Nelson Denny scores, respectively. Mean semester average, mean score of the Mosby test, mean number of semester tests failed, and age above thirty-three were the most significant predictors of white graduates' NCLEX success. Older graduates had a higher mean Mosby score, a higher mean semester average, and failed fewer semester tests than younger graduates. The study results will be of interest to nurse educators and counselors who are concerned with curricular revision, student counseling, and remediation procedures as these relate to enhancement of graduates' potential for success on the NCLEX.

In today’s education, occupational (economic) life is the focus of our attention. We want every child to succeed, and this has come to mean that every child should be pre­pared for college and the sort of work that requires a col­lege education. What of all the children who will become bus and truck drivers, retail sales clerks, appliance repair people, construction workers, materials handlers, heavy equipment operators, railway engineers and conductors, house painters, plumbers, bakers, farm workers, beauti­cians, postal workers, cooks, waiters, hotel clerks, house and office cleaners, auto mechanics and sales people, dog and horse groomers, telephone/ electric line work­ers, prison guards, hospital attendants, grounds keepers, maintenance workers, managers of laundromats and dry cleaning shops, installers of burglar alarms, carpet layers, window washers, steel workers, fishermen, sailors, cater­ers, cashiers, chimney sweeps, roofers, makers of china and glassware, decorators, musicians, florists, entertainers, moving men . . . and what would happen to our society if no one were willing to do this work? Do these people represent failures of schooling, or do we fail them when we lead them to believe that only economic success is suc­cess? Teachers and parents can lose perspective when achievement is narrowly defined. What messages are we sending students when grades, test scores, and academic achievement are the criteria for “success” during their twelve plus years of schooling? Many students who struggle in school thrive in their families, communities, and jobs once they leave school. For some, leav­ing school may be the first time they experience real success and a sense of personal, task- related satisfaction. As we teach them and before they leave us, have we given these “non- achieving” students hope that they will have the tenacity to excel? Confidence that they will find their path? Courage to trust their ability to figure it out? Many students struggle with undiagnosed anomalies that limit their capacity to learn school subjects. For those students whose minds cannot adjust to the “book learning” of schools, do we still communicate that we want the best for them? Do we let them know that they are worthy of our support and encourage­ment for their future? Do we let students know they are valued whether or not they meet our academic expectations?