scholarly journals Examining Some of Students’ Views on the Nature of Science (NOS) in Traditional Lecture Format Teaching Environment

2021 ◽  
Vol 5 (2) ◽  
pp. 69-77
Author(s):  
Issa I. Salame ◽  
Shirley Dong
Keyword(s):  
Grade Point Average ◽  
Science Teaching ◽  
Nature Of Science ◽  
Teaching And Learning ◽  
Science Research ◽  
Learning Activities ◽  
Background Information ◽  
Algorithmic Problem ◽  
Grade Point ◽  
Science Courses

The preparation of a scientifically literate society is the main goal of science education throughout the world and this has resulted in the emphasis of nature of science in the curriculum. The purpose of this research project is to examine the aforementioned students’ views on NOS tenets, its relationship to their academic achievements and background, and how it changes through their study of science. The study took place at the City College of New York, an urban, commuter, public college, and minority serving institute. The research data was collected through the administration of a survey that contained three of the NOS questions and academic and background information about the students. The data suggest that students possess inadequate understanding of the nature of science when they begin their academic fields of science study. This inadequate understanding is resistant to change in traditional science teaching settings. The data provide evidence that the inadequate understanding of nature of science does not change as the result of exposure to science courses, the field of science studied, and the students’ academic achievement as measured by grade point average. Our data show that traditional instruction in college science courses does not address nature of science and does not cause a conceptual change in the students’ understanding of NOS. The lack of correlation between students’ understanding of nature of science and credits completed or grade point average could be attributed to students relying on rote-learning and algorithmic problem-solving to achieve high grades and succeed in science, which hinders their meaningful learning of science and the development of conceptual understanding. Thus, science teaching and instruction should address naïve conception on the NOS and changes the instruction methods to consider NOS naïve conceptions and learning challenges. Science teaching and learning curriculum and instruction should immerse students in science learning activities that nurtures their understanding of the nature of science through participating in novel science research and inquiry-based learning activities.

scholarly journals Virtual and in‐person teaching and learning activities for core food science courses

2021 ◽  
Vol 20 (2) ◽  
pp. 72-75
Author(s):  
Patricia Hingston ◽  
Rosalia Garcia‐Torres ◽  
Vinay Mannam
Keyword(s):  
Teaching And Learning ◽  
Learning Activities ◽  
Food Science ◽  
Science Courses

Learners' Cognitive Styles and Psychological Types as Intervening Variables Influencing Performance in Computer Science Courses

1987 ◽  
Vol 15 (4) ◽  
pp. 391-399 ◽  
Author(s):  
Sarla Sharma
Keyword(s):  
Academic Success ◽  
Computer Science ◽  
Cognitive Styles ◽  
Academic Program ◽  
Grade Point Averages ◽  
Background Information ◽  
Grade Point ◽  
Psychological Types ◽  
Science Courses ◽  
Computer Science Courses

During the past twenty years, many educators have tried to incorporate technological progress and processes into the nation's schools. As the demand for computer science courses continues its phenomenal growth into the 1980s, the problems of identifying components of computer science aptitude and predicting academic success in computer science courses become increasingly important. This article is based on the critical analysis of the most recent research studies concerning the identification of components of computer science aptitude responsible for success in computer science courses. The analysis attempts to answer three questions: 1. Do certain cognitive styles have a bearing on performance in computer science courses?; 2. Do certain psychological types have bearing on performance in computer science courses?, and 3. Do certain background variables (sex, age, academic classification, prior computer experience, academic program, and high school and college grade point averages) have relevance for performance in computer science courses? Finally, implications for matching curriculum and instructional strategies with students' different cognitive styles, personality types, and background information are presented and suggestions for advisement and placement of prospective computer science students, and recommendations for further research in this area are made.

scholarly journals Grappling with the Literature of Education Research and Practice

2007 ◽  
Vol 6 (4) ◽  
pp. 289-296 ◽  
Author(s):  
Erin L. Dolan
Keyword(s):  
Education Research ◽  
Science Teaching ◽  
Teaching And Learning ◽  
Life Sciences ◽  
Science Research ◽  
Research Literature ◽  
Regular Feature ◽  
Science Teaching And Learning ◽  
Research And Practice ◽  
Specialized Language

The absence of a central database and use of specialized language hinder nonexperts in becoming familiar with the science teaching and learning literature and using it to inform their work. The challenge of locating articles related to a specific question or problem, coupled with the difficulty of comprehending findings based on a variety of different perspectives and practices, can be prohibitively difficult. As I have transitioned from bench to classroom-based research, I have become familiar with how to locate, decipher, and evaluate the education research literature. In this essay, I point out analogies to the literature of science research and practice, and I reference some of the literature that I have found useful in becoming an education researcher. I also introduce a new regular feature, “Current Insights: Recent Research in Science Teaching and Learning,” which is designed to point CBE—Life Sciences Education (CBE-LSE) readers to current articles of interest in life sciences education, as well as more general and noteworthy publications in education research.

scholarly journals Predicting key educational outcomes in academic trajectories: a machine-learning approach

2020 ◽  
Vol 80 (5) ◽  
pp. 875-894 ◽  
Author(s):  
Mariel F. Musso ◽  
Carlos Felipe Rodríguez Hernández ◽  
Eduardo C. Cascallar
Keyword(s):  
Machine Learning ◽  
Grade Point Average ◽  
Learning Strategies ◽  
Degree Completion ◽  
Educational Outcomes ◽  
Background Information ◽  
Grade Point ◽  
Methodological Approaches ◽  
Artificial Neural ◽  
Academic Retention

Abstract Predicting and understanding different key outcomes in a student’s academic trajectory such as grade point average, academic retention, and degree completion would allow targeted intervention programs in higher education. Most of the predictive models developed for those key outcomes have been based on traditional methodological approaches. However, these models assume linear relationships between variables and do not always yield accurate predictive classifications. On the other hand, the use of machine-learning approaches such as artificial neural networks has been very effective in the classification of various educational outcomes, overcoming the limitations of traditional methodological approaches. In this study, multilayer perceptron artificial neural network models, with a backpropagation algorithm, were developed to classify levels of grade point average, academic retention, and degree completion outcomes in a sample of 655 students from a private university. Findings showed a high level of accuracy for all the classifications. Among the predictors, learning strategies had the greatest contribution for the prediction of grade point average. Coping strategies were the best predictors for degree completion, and background information had the largest predictive weight for the identification of students who will drop out or not from the university programs.

scholarly journals MENYOAL PEMBELAJARAN SAINS DI SEKOLAH: BAGAIMANA SEHARUSNYA?

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Tomo Djudin
Keyword(s):  
Science Teaching ◽  
Nature Of Science ◽  
Learning Process ◽  
Science And Technology ◽  
Learning Activities ◽  
Science Text ◽  
Teaching Learning

Teachers understanding on the nature of science will determine types of students learning activities in the class. In designing a science teaching-learning process meaningfully, a teacher should consider and pay attention to the learning activities. They are (1) logical plane activities; (2) evidental or experiental plane activities; (3) psychological plane activities. A science text-books centered teaching should be modified because, the students comprehension about science products (concept and principles) could not be developed meaningfully by using text-books only. This culture is also contrary with the nature of science and is not able to build a science and technology literate people.Key words: Teachers understanding; learning activities

Do High School Athletes Get Better Grades During the Off-Season?

2016 ◽  
Vol 18 (2) ◽  
pp. 182-208 ◽  
Author(s):  
Katie Schultz
Keyword(s):  
Academic Performance ◽  
Grade Point Average ◽  
Time Allocation ◽  
Leisure Activities ◽  
High School Athletes ◽  
Market Outcomes ◽  
Grade Point ◽  
Science Courses ◽  
Positive Effects ◽  
Varsity Athletes

A great deal of recent research has employed instrumental variables to estimate the effect of participation in athletics on academic or labor market outcomes, finding evidence of small positive effects from participation. This research proposes several theories of how participation affects success but cannot distinguish between them. I ask a fundamentally different question, whether an athlete performs better or worse, academically, during the season in which they participate in sports, focusing on the time allocation theory of participation. Time spent on sports may substitute from time on academics or negative leisure activities, causing academic performance to improve or decline in-season, respectively. This paper finds a small negative and significant in-season effect on academic performance for varsity athletes and a small positive and significant in-season effect on academic performance for junior varsity (JV) athletes. Decreases in in-season grade point average (GPA) for varsity athletes occur through a decline in performance in English and history courses, while increases in in-season GPA for JV athletes operate through an improvement in math and science courses. Results are robust to controlling for various measures of course ease across semesters. The relatively small in-season effects suggest that estimates of the effects of participation in the rest of the literature operate primarily through mechanisms other than time allocation.

Paket Program, Indeks Prestasi Kumulatif, Umur dan Domisili sebagai Faktor Pembeda Prestasi Akademik Mahasiswa

2021 ◽  
Vol 13 (1) ◽  
pp. 224
Author(s):  
Supriyanto Supriyanto ◽  
Dewi Anggraini ◽  
Fahmi Sulaiman ◽  
Elserra Siemin Ciamas ◽  
Yeni Rachmawati
Keyword(s):  
Academic Achievement ◽  
Grade Point Average ◽  
Canonical Correlation ◽  
Teaching And Learning ◽  
Program Package ◽  
Student Academic Achievement ◽  
Prospective Students ◽  
Tertiary Institution ◽  
Grade Point ◽  
Tertiary Institutions

One measure of success in teaching and learning in tertiary institutions is academic achievement. Through student academic achievement, it will increase the enthusiasm of prospective students in determining the tertiary institution of their choice. This research is aimed to determine the differentiating factors of student academic achievement, with the independent variables, namely Program Package, Grade Point Average (GPA), Age and Domicile. The research conducted included classifying students into two groups based on student academic achievement, so the analysis method used was Discriminant Analysis. The results revealed that the differentiating variables between groups consisted of (1) Grade Point Average and (2) Age. The results of data processing from the Enter / Removed Variables, it is known that the Grade Point Average (GPA) variable can be included in the discriminant equation formation process, while the Program Package, Age, and Domicile variables cannot be included in the discriminant equation formation. Eigenvalues test results, obtained a Canonical Correlation value of 0.852 so that the Square Canonical Correlation (CR2) = (0.852) 2 = 0.7259, it can be concluded that the Student Academic Achievement Variable can be explained by the Variable Program Package, Student Achievement Index (GPA), Age and domicile of 72.59%. The results of the validation state that the level of accuracy is> 50% so that the discriminant function is considered appropriate in classifying students.

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