ATTITUDES RELATED TO STUDENTS’ PERFORMANCE IN STATISTICS IN UNIVERSITY PROGRAMS IN ARGENTINA

Students from non-statistics degree programs often perceive statistics as a burden, underestimating its usefulness and encountering difficulties that cause them anxiety and stress, among others, which leads many of them to fail the course. Students’ attitudes can hinder their learning and development of useful skills associated with statistical thinking, which should be later applied outside the classroom. The aim of this study was to analyze students’ attitudes towards statistics in introductory courses in three schools of Argentina, grouped in Agricultural Sciences and Biological Sciences. We analyzed students’ attitudes at the beginning and at the end of the course, the differences between pre- and post-course attitudes and the relationship between these changes and students’ performances. The sample consisted of 436 students and their attitudes were measured using the Survey of Attitudes Towards Statistics (SATS-28), considering four components: Affect, Cognitive Competence, Value and Difficulty. Students’ performances were classified as: passed (and exempt from final exam), intermediate (but not exempt from final exam), and failed. Difficulty was not related to students’ performance, as opposed to what was detected with the other components. Cognitive competence was the only component that classified students’ performance in the correct order. Students who failed the course differed from the rest in that they developed more negative feelings towards statistics at the end of the course; in contrast, students with good performance showed an increase in the value given to statistics. Biological Sciences students presented higher average in the four components studied. Abstract: Spanish Los estudiantes de carreras universitarias no estadísticas a menudo perciben a estadística como una imposición, subestimando su utilidad, encontrando dificultades que les causan, entre otros, ansiedad y estrés y muchos desaprueban la materia. Las actitudes de los estudiantes pueden dificultar su aprendizaje y el desarrollo de habilidades útiles asociadas al pensamiento estadístico que deberían aplicarse posteriormente fuera del aula. El objetivo de este estudio fue analizar las actitudes de los estudiantes hacia la estadística en cursos introductorios en tres facultades de Argentina, agrupadas en Ciencias Agrícolas y Ciencias Biológicas. Analizamos sus actitudes al principio y al final del curso, las diferencias entre las actitudes posteriores y previas al curso y la relación entre estos cambios y el rendimiento del alumno. La muestra estaba compuesta por 436 estudiantes y sus actitudes se midieron utilizando la Encuesta de Actitudes Hacia la Estadística (SATS-28), considerando cuatro componentes: Afecto, Competencia Cognitiva, Valor y Dificultad. El rendimiento de los estudiantes se clasificó en promoción, intermedio y reprobación. Dificultad no se relacionó con el rendimiento del estudiante a diferencia con lo detectado con las otras componentes. La Competencia Cognitiva fue la única componente que clasificó el rendimiento en el orden correcto. Los estudiantes que reprobaron el curso se diferenciaron del resto en que desarrollaron más sentimientos negativos hacia la estadística al final del curso; en contraposición los que tuvieron un buen rendimiento, mostraron un aumento en el valor dado a la estadística. Los estudiantes de Ciencias Biológicas presentaron un promedio más alto en las cuatro componentes.

Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review

One of the ultimate goals of the learning process is the success of student learning. Using data and students' achievement with machine learning to predict the success of student learning will be a crucial contribution to everyone involved in determining appropriate strategies to help students perform. The selected 11 research articles were chosen using the inclusion criteria from 2753 articles from the IEEE Access and Science Direct database that was dated within 2019-2021 and 285 articles that were research articles. This study found that the classification machine learning algorithm was most often used in predicting the success of students' learning. Four algorithms that were used most often to predict the success of students' learning are ANN, Naïve Bayes, Logistic Regression, SVM and Decision Tree. Meanwhile, the data used in these research articles predominantly classified students' success in learning into two or three categories which are pass/fail; or fail/pass/excellent.

Feeling exhausted and isolated? The connections between university students’ remote teaching experiences, motivation, and psychological well-being during the COVID-19 pandemic

We investigated university students’ remote teaching experiences, how they predict psychological well-being, and whether the predictions vary depending on students’ motivation. Self-reports were collected from Finnish university students (N = 2686). Within the latent variable modeling framework, we classified students according to their expectancy-value-cost profiles, compared latent means, and tested whether the predictions differed across groups. Six groups described the data best: moderately motivated, utility-oriented, disengaged, indifferent, positively ambitious, and struggling ambitious. The groups differed significantly on remote teaching experiences and well-being, but predictions were similar across the groups: Engagement was predicted positively by evaluation of remote teaching and negatively by perceived strain, exhaustion positively by evaluation of teaching and perceived strain, and depressive symptoms by perceived strain and sense of alienation. Findings suggest that remote teaching experiences during the pandemic contribute to students’ psychological well-being in distinct ways, and that certain motivational mindsets might buffer against the negative effects.

Missed Opportunity: How Induction Policy Fails to Explicitly Address English Learner-Classified Students

English Learner-classified (ELC) students are one of the nation’s most marginalized student populations. One promising but understudied strategy to strengthen teaching of ELC students is teacher induction. This article examines the role of teacher induction in strengthening novice teachers’ EL-specific teaching knowledge and skills. Through a detailed analysis of induction in California, we find that the state has little external assurance that teachers who have undergone induction can meet ELC students’ unique and diverse needs. California’s decentralized, flexible, teacher-led induction may support teachers’ development of general teaching skills, but misses an opportunity to support teachers in an area where many of them struggle. The study raises other problematic issues around mentoring for equity such as monolithic views of ELC students, lack of timely and actionable information about language proficiency, and lack of guidance as to what constitutes acceptable evidence of competency teaching ELC students.

Knowledge and Habits of Exercise in Medical Students

Objective. To examine the exercise habits, knowledge, and self-efficacy of incoming medical students. Methods. Mixed-methods study consisting of (1) cross-sectional surveys and (2) qualitative key-informant interviews. (1) International Physical Activity Questionnaire (IPAQ), American Adult’s Knowledge of Exercise Recommendations Survey (AAKERS), and Self-Efficacy for Exercise Scale (SEES) to assess student’s physical activity level, knowledge of exercise recommendations, and self-efficacy for exercise. (2) Scripted questions explored exercise habits, sources of exercise knowledge, attitude toward exercise. Results. (1) Results of IPAQ classified students as 50% having high, 40% moderate, and 10% low levels of physical activity (n = 132). AAKERS demonstrated a mean total score of 16.2/20 (n = 130) (81% correct), similar to the national average (mean = 16/20) (n = 2002). SEES mean score of 48.5/90 (n = 128) is similar to previous studies (mean = 48.6/90, 52.75/90). (2) Interviews revealed that most students have a consistent exercise routine. Few students received formal education in exercise (10%), while the rest cited either peers, sports, or internet as primary sources of exercise knowledge. Less than half stated they would be comfortable designing an exercise routine for patients. Conclusions. Incoming medical students live an active lifestyle but have limited knowledge and formal training in exercise. Student’s knowledge is predominantly self-taught from independent resources.

Problemas de exámenes y soluciones XXX Olimpiada Costarricense de Matemática, 2018

OLCOMA es la Comisión de Olimpiadas Costarricenses de Matemáticas. Esta comisión está conformada por académicos en el área de Matemática de la Universidad Nacional, del Instituto Tecnológico de Costa Rica, de la Universidad de Costa Rica, de la Universidad Estatal a Distancia, y por representantes del Ministerio de Educación Pública y del Ministerio de Ciencia, Tecnología y Telecomunicaciones. Dentro de la estructura de las Olimpiadas Costarricenses de Matemáticas, se tienen tres niveles de competencia. En Nivel I participan estudiantes de sétimo año, entre 10 y 13 años, aproximadamente (también pueden optar por participar en este nivel los estudiantes de primaria que cursan sexto grado). En Nivel II participan estudiantes de octavo y noveno años, entre 14 y 15 aõs, aproximadamente. En Nivel III participan estudiantes de décimo, undécimo y duodécimo años, más de 15 años. Durante el año 2017, se trabajó con tres etapas. En la I Eliminatoria los estudiantes resolvieron un examen de selección única con 25 ítems. En la II Eliminatoria, los clasificados realizaron un examen con 12 preguntas de selección única y tres problemas de desarrollo. En la Etapa Final, los estudiantes clasificados realizaron dos pruebas en días consecutivos, cada prueba con tres problemas de desarrollo. El objetivo de este libro es que los futuros participantes en Olimpiadas Costarricenses de Matemáticas posean material de consulta. Los problemas que en este libro se enuncian representan un reto para quienes gustan resolver ejercicios matemáticos. Cada uno de los problemas tiene la solución respectiva, así que una vez que intenten resolver cada problema, pueden comparar el procedimiento realizado con la solución propuesta. Se han incorporado todos los problemas de I Eliminatoria para cada uno de los tres niveles, los problemas de II Eliminatoria para cada uno de los tres niveles, los problemas propuestos para conformar los exámenes de la Etapa Final y los problemas que conformaron los exámenes de la Etapa Final. Abstract OLCOMA is the Costa Rican Mathematics Olympics Commission. This commission is made up of academics in the area of Mathematics from the Universidad Nacional, the Instituto Tecnológico de Costa Rica, the Universidad de Costa Rica, the Universidad Estatal a Distancia, and the Universidad Autónoma de Costa Rica and by representatives of the Ministry of Public Education and of the Ministry of Science, Technology, Culture and TelecomuncationsWithin the structure of the Costa Rican Mathematical Olympiads, there are three levels of competition. In Level I there are students of seventh year, between 10 and 13 years old, approximately (also the students of primary school that are studying in this level can choose to participate in this level sixth grade). In Level II, students of eighth and ninth years, between 14 and 15 years, approximately, participate. In Level III there are students of tenth, eleventh and twelfth years, plus 15 years old. During the year 2017, we worked with three stages. In the First Elimination, the students resolved toa single selection test with 25 items. In the II Eliminatory, the classified ones carried out aexam with 12 single-choice questions and three developmental problems. In the Final Stage, the classified students took two tests on consecutive days, each test with three tests developmental problems. The objective of this book is that future participants in Costa Rican Mathematics Olympiads possess reference material. The problems listed in this book represent a challenge for those who like to solve mathematical exercises. Each of the problems has the respective solution, so once who try to solve each problem, can compare the procedure carried out with the proposed solution. All the problems of I Eliminatory for each one of the three levels, the problems of II Eliminatory for each one of the three levels, the problems proposed to conform the examinations of the Final Stage and the problems that conformed the examinations of the Final Stage have been incorporated.

Guide Teaching System Based on Artificial Intelligence

To improve the development and deployment efficiency of the system, this paper combined the software system with Java and AI language Prolog to achieve the guide teaching system based on artificial intel-ligence (AI). The system creatively adopted the theory of artificial intelligence expert system, at the same time, built a Struts+Spring+Hibernate lightweight JavaEE framework. The coupling degree of each module in the system was greatly reduced to facilitate the expansion of future functions. Based on the development principle of the artificial intelligence expert system, the system diagnosed the learner's mastery of each point of knowledge. It classified students' learning effect and evaluated the knowledge points. Making full use of the learning state of students and combining it with artificial intelligence expert system theory, the system developed a suitable learning strategy to help students improve their learning with less efforts. In addition, the system took the forgetting rule of human brain into account, which periodically presented trainees’ knowledge points assessment and avoided students wasting time. The purpose was to help students improve their learning effect. Finally, the system was tested. The test results showed that the system is applicable and useful. It is concluded that the artificial intelligence system provides an example for the same method and has certain reference significance.

A Brief Analysis on Error in Indonesian Beginner Level Students’ Chinese Composition

Indonesian Chinese students at beginner level often encounter difficulties in writing. Qualitative research is used in this article, through the collection of midterm essays from first-year Binus University students, the author classified students’ error in writing into some categories, and analyzed them to help teachers and students during the Chinese Writing Class. During the Chinese writing learning process research found out that there are errors occur in wrong usage of word usage, punctuation, Chinese character writing, and the error of addition, omission, ordering, and selection are commonly found in grammatical errors.

Approach-Avoidance Individual Differences in Changing Students' Responses to Physical Education

The purpose of this report was to examine the effects of physical education acrobatic activities as a function of individual differences on approach-avoidance tendencies for acrobatics. The data of a study conducted by Robazza, Bortoli, Carraro, and Bertollo (2006) were analyzed after having classified students as high- or low-avoiders. Approach-avoidance tendencies and idiosyncratic emotions related to acrobatic tasks and adventurous sports were originally assessed for 72 Italian male high school students. Experimental participants engaged in acrobatic tasks of physical education for 12 lessons, while control participants were involved in team sports. Analysis showed that high-avoiders changed their emotions positively toward physical education tasks more than low-avoiders, whereas the latter modified their attitudes for adventurous sports. Approach-avoidance tendencies can be expected to moderate involvement in challenging physical activities.

Social-Affective Characteristics in Early Adolescents Identified as Learning Disabled and Nondisabled

This study examined social-affective characteristics, including loneliness, self-concept, integration, victimization, participation, and teacher-rated social competence across groups identified as either learning disabled or nondisabled. Subjects were students in middle schools, and the pupils with learning disabilities were enrolled in resource room special education programs. Results indicated that the two comparison groups differed significantly on every measure except self-concept. Variable intercorrelations were also different across groups. Moreover, certain linear combinations of scores on the dependent measures accurately classified students into each of the comparison groups. The results are discussed in terms of the need for comprehensive assessment and treatment of students who present social-affective problems in school.