Factors influencing success in introductory college chemistry

Tai, Robert H.; Sadler, Philip M.; Loehr, John F.

doi:10.1002/tea.20082

Cited by 122 publications

(154 citation statements)

References 37 publications

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“…Wagner et al, 2002;Lewis and Lewis, 2007). Students' prior academic performances in mathematics and chemistry have a moderately strong correlation with performance in first-year chemistry (McFate and Olmsted, 1999;Evans, 2000;McKenzie and Schweitzer, 2001;Wagner et al, 2002;Thai et al, 2005). Similarly, the cognitive variable, logical reasoning ability is as successful for the prediction of success in tertiary chemistry as SAT scores (Bunce and Hutchinson, 1993).…”

Section: Introductionmentioning

confidence: 99%

Inaccuracy of self-evaluation as additional variable for prediction of students at risk of failing first-year chemistry

Potgieter¹,

Ackermann²,

Fletcher³

2010

Chem. Educ. Res. Pract.

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Early identification of students at risk of failing first-year chemistry allows timely intervention. Cognitive factors alone are insufficient predictors for success; however, non-cognitive factors are usually difficult to measure. We have explored the use of demographic and performance variables, as well as the accuracy of self-evaluation as an indicator of metacognitive ability, as possible indicators for students at risk of failing the first semester course in General Chemistry (CMY 117) at the University of Pretoria. Variables with a strong correlation with performance in CMY 117 were used to develop a prediction model based on logistic regression. Three variables, i.e. prior performance in mathematics and in physical science, and the extent of overconfidence expressed as the ratio between expected and actual performance in a chemistry pre-test written at the start of the semester, were shown to be significant predictors for risk of failing. The highest overall accuracy of prediction (76%) was obtained for a subset of students with a C or D grade for their high school leaving examination in mathematics when high risk students were defined as those with a final mark for CMY 117 as 51% or lower. The prediction model, based on the model building data set, had a sensitivity of 92% and a specificity of 46%; whilst the sensitivity and specificity using the validation data set were 88% and 38% respectively.

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Section: Introductionmentioning

confidence: 99%

Inaccuracy of self-evaluation as additional variable for prediction of students at risk of failing first-year chemistry

Potgieter¹,

Ackermann²,

Fletcher³

2010

Chem. Educ. Res. Pract.

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“…The learner, himself is a central factor in determining whether meaningful learning will take place or not. This may include his background, motivation, age, sex or gender, personality, cognitive style and so on (Tai, Sadler and Loehr(2005), Ogunleye(2011), Alavi andHoseini, 2009, Bassey, Umoren andUdida,2013 ) According to Miller (1987) cognitive styles represent the individual differences in the various subcomponents of an information-processing model of three main cognitive processes: perception, memory, and thought. He argued that "all of the cognitive styles are subordinate to, and reflect, a broad super ordinate stylistic (analytic-holistic) difference".…”

Section: Introductionmentioning

confidence: 99%

Influence of Cognitive Style and Gender on Secondary School Students’ Achievement in and Attitude to Chemistry

Idika¹

2017

ASSRJ

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The purpose of the study was to determine the influence of two major cognitive styles (Field Dependent and Field independent) and gender on students' achievement in and attitude to chemistry. A total of two hundred and eight (208) SSII chemistry students drawn from some selected secondary schools in three local government areas in Ibadan, Oyo state, Nigeria participated in the study. Three instruments were employed in this research. They are Cognitive Style Checklist (r=0.84), Chemistry Achievement Test(r=0.81) and Students' Attitude to Chemistry Questionnaire(r=0.84). This was a survey research. Four hypotheses were tested at 0.05 level of significance and data collected were analyzed using Descriptive Statistics and t-test. The results showed that there was significant main difference between on field dependent and field independent students' achievement in chemistry (t(1,207) = 5.173; P < 0.05]; students with field independent level of cognitive style obtained higher mean score of chemistry achievement ( = 8.89) than those with field dependent level of cognitive style ( = 8.19); there was no significant main difference between field dependent and field independent students' attitude to chemistry [t(1,207) = 1.271; P>0.05] ; there was no significant main difference between male and female students' achievement in chemistry [t(1,207) = .704; P>.05] but the female students obtained higher mean achievement score ( = 98.64) than their male counterparts ( = 98.28); there was significant main difference between male and female students' attitude to chemistry [t(1,207) = 18.041; P<0.05]. Cognitive style can affect students' achievement in chemistry and those of the field independent category perform better than those of the field dependent category; whereas, cognitive style has no influence on students' attitude to chemistry. Even though, male and female students do not differ much in their achievement in chemistry, their attitude of the female students to chemistry is better than that of the male students. Therefore, it is recommended that teachers have adequate knowledge of the dominant cognitive style category in their classes as this could facilitate and ensure more meaningful learning as well as serve as guide for selection of teaching methods. In addition, chemistry teachers should make efforts in ensuring that chemistry classes are interesting and appealing to their male students.

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“…Resultado semelhante foi observado em Física 2. A menor importância do professor, em relação a outros elementos que afetam o rendimento dos alunos já havia sido observada anteriormente [23,28]. Por outro lado a nota média depende fortemente do curso do qual procedem os alunos que compõem cada turma.…”

Section: Todos Os Professoresunclassified

Aumento na quantidade de alunos em disciplinas básicas: Como obter vantagens dessa realidade universitária

Mello

2015

Rev. Bras. Ensino Fís.

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A queda na qualidade de ensinoé muitas vezes considerada uma consequência inevitável do aumento no número de alunos atendidos por uma disciplina universitária. No entanto, unificar a avaliação e outros elementos envolvidos com as disciplinas pode trazer ganhos em vários níveis do processo pedagógico. Para tratar desse assunto, esse artigo divide-se em duas partes: a primeira discute a implementação da unificação das disciplinas de Física-1 e Física-2, e a segunda analisa, estatisticamente, os resultados obtidos. São apresentadas técnicas que podem ser utilizadas para lidar com um grande número de alunos de maneira satisfatória, a maior parte delas baseadas no uso de ferramentas computacionais, adotadas no Instituto de Física da Universidade de Brasília para melhorar a formação dos alunos e a utilização dos recursos humanos.É apresentada a demanda de trabalho envolvida na unificação, permitindo avaliar a sua viabilidade em outras instituições. Diversas análises são realizadas a partir dos dados dos alunos da unificação, para determinar como a taxa de abandono e o desempenho dos alunos depende do professor, do comprometimento dos alunos com a disciplina, da existência de uma prova final e da formação pregressa do aluno. Ao final, fica demonstrado que o aumento na quantidade de alunos, aliadoà adoção de práticas pedagógica unificadas, pode trazer benefícios ao processo como um todo. Palavras-chave: disciplinas básicas do curso superior, avaliação, informática educacional.The decline in the quality of education is often considered an inevitable consequence of increasing the number of students of the university courses. However, the unification of assessments and other changes in the courses can bring gains at various levels of the educational process. In order to address this issue, this article is divided into two parts: the first part discusses the implementation of the unification of the disciplines of Physics 1 and Physics 2, and the second part is a statistical analysis of results. Techniques are presented that can be used to satisfactorily handle a large number of students. Most of them are based on computational tools, and were used at the Physics Institute at the University of Brasilia to improve the training of students and the use of human resources. It is discussed the effort to propose this unification in other institutions. Several analyzes are performed from the data of students, in order to determine how the dropout rate and student performance depends on the teacher, on the commitment of students with the course, on the existence of a final exam, and on the educational background of the students. Finally, it is shown that the increase in the number of students, coupled with the adoption of unified pedagogical practices, can bring benefits to the whole educational process.

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Factors influencing success in introductory college chemistry

Cited by 122 publications

References 37 publications

Inaccuracy of self-evaluation as additional variable for prediction of students at risk of failing first-year chemistry

Inaccuracy of self-evaluation as additional variable for prediction of students at risk of failing first-year chemistry

Influence of Cognitive Style and Gender on Secondary School Students’ Achievement in and Attitude to Chemistry

Aumento na quantidade de alunos em disciplinas básicas: Como obter vantagens dessa realidade universitária

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