Reforming the Teaching and Learning of Foundational Mathematics Courses: An Investigation into the Status Quo of Teaching, Feedback Delivery, and Assessment in a First-Year Calculus Course
Abstract:Several universities are witnessing an increase in students’ enrolment in mathematics-intensive programmes over the last decades. This increase has come with the price of high failure rates in foundational mathematics courses, which poses challenges to mathematics teaching and learning in higher education. It is therefore inevitable, for some universities, to transform the teaching and learning of mathematics to more student-centred approaches that engage the students mathematically and enhance their success r… Show more
“…Mathematics for first-year undergraduate students otherwise called foundational mathematics courses is crucial not only in bridging pre-university and university mathematics experience but also in shaping higher courses in mathematics-intensive university programmes. However, an accumulation of evidence suggests that students following mathematics-intensive university programmes, e.g., science, technology, engineering, or mathematics (STEM) courses find it difficult to pass foundational mathematics courses around the world ( Ellis et al, 2016 ; Bigotte de Almeida et al, 2021 ; Zakariya et al, 2022a ). This poor performance in foundational mathematics courses has many consequences in higher education such as increased absenteeism, non-completion of degrees, change of majors (usually from STEM to non-STEM programmes), and development of negative attitudes towards mathematics ( Ellis et al, 2016 ; Bigotte de Almeida et al, 2021 ).…”
We assess students’ approaches to learning mathematics not only to predict students’ learning outcomes but also for its crucial utilities in the teaching and learning process. These utilities range from evaluating effective instructional interventions, determining students with learning difficulties, and comparing teaching and learning experience in higher education. However, measures of the constructs have raised validity concerns among researchers. A root cause of these validity concerns is traceable to the failure of these measures to account for the content-specificity of approaches to learning. Building on a previously developed general measure of the constructs, I designed this study to bridge this gap by developing and validating approaches to learning mathematics questionnaire (ALMQ). 352 first-year engineering students who gave voluntary consent participated in the study. The students were mainly males with ages ranging from 15 years to 29 years. The average age was 20.67 years, and its standard deviation was 2.164. I analysed the generated data using confirmatory factor analysis and judged the consistency of hypothesised models with the generated data using a combination of criteria. The findings revealed a two-factor ALMQ with seven items which demonstrated an excellent global and local fit of the generated data. The standardised factor loadings for all the items were above 0.68 with an average of 0.73 showing the high strengths of the items in measuring their respective constructs. I also found a reliability coefficient of 0.81 for deep approaches, 0.77 for surface approaches, and 0.72 for the two-factor ALMQ. These findings suggest preliminary evidence of the validity and reliability of ALMQ. I discussed the practical implications of the findings for educators, policymakers, and researchers interested in improving the mathematics learning experience.
“…Mathematics for first-year undergraduate students otherwise called foundational mathematics courses is crucial not only in bridging pre-university and university mathematics experience but also in shaping higher courses in mathematics-intensive university programmes. However, an accumulation of evidence suggests that students following mathematics-intensive university programmes, e.g., science, technology, engineering, or mathematics (STEM) courses find it difficult to pass foundational mathematics courses around the world ( Ellis et al, 2016 ; Bigotte de Almeida et al, 2021 ; Zakariya et al, 2022a ). This poor performance in foundational mathematics courses has many consequences in higher education such as increased absenteeism, non-completion of degrees, change of majors (usually from STEM to non-STEM programmes), and development of negative attitudes towards mathematics ( Ellis et al, 2016 ; Bigotte de Almeida et al, 2021 ).…”
We assess students’ approaches to learning mathematics not only to predict students’ learning outcomes but also for its crucial utilities in the teaching and learning process. These utilities range from evaluating effective instructional interventions, determining students with learning difficulties, and comparing teaching and learning experience in higher education. However, measures of the constructs have raised validity concerns among researchers. A root cause of these validity concerns is traceable to the failure of these measures to account for the content-specificity of approaches to learning. Building on a previously developed general measure of the constructs, I designed this study to bridge this gap by developing and validating approaches to learning mathematics questionnaire (ALMQ). 352 first-year engineering students who gave voluntary consent participated in the study. The students were mainly males with ages ranging from 15 years to 29 years. The average age was 20.67 years, and its standard deviation was 2.164. I analysed the generated data using confirmatory factor analysis and judged the consistency of hypothesised models with the generated data using a combination of criteria. The findings revealed a two-factor ALMQ with seven items which demonstrated an excellent global and local fit of the generated data. The standardised factor loadings for all the items were above 0.68 with an average of 0.73 showing the high strengths of the items in measuring their respective constructs. I also found a reliability coefficient of 0.81 for deep approaches, 0.77 for surface approaches, and 0.72 for the two-factor ALMQ. These findings suggest preliminary evidence of the validity and reliability of ALMQ. I discussed the practical implications of the findings for educators, policymakers, and researchers interested in improving the mathematics learning experience.
“…Some studies were dedicated to improve statistical education, mainly centering on the use of technology, teaching method, and teaching content (Smith, 1998;Bordley and Robert, 2001;Mills, 2002;Zakariya and Bamidele, 2016;Zakariya et al, 2021). The prior researches have played an important role in improving the effectiveness of statistics teaching.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, these courses will also contribute in quantitative research and comprehension of empirical study. However, many higher education institutions have to cope with high failure rates in statistics-related courses ( Smith et al, 2021 ; Zakariya et al, 2022 ). This poses a severe challenge to teaching and learning for these courses in higher education.…”
Section: Introductionmentioning
confidence: 99%
“…The prior researches have played an important role in improving the effectiveness of statistics teaching. However, these teachings were dominated by teacher-directed instruction and note-taking, resulting in learning difficulty for students during class activities ( Zakariya et al, 2022 ). Additional investigations have been focused on non-cognitive characteristics of college students, and showed that attitudes and beliefs toward statistics play an important role in the success or failure of the learning process ( Gal and Ginsburg, 1994 ; Seipel and Apigian, 2005 ).…”
The influence of perfectionism and statistics anxiety on academic performance (AP) in statistics courses was investigated using a multidimensional perfectionism scale and a statistics anxiety rating scale. For perfectionism, the factor of personal standards (PS) had a significant direct positive effect on AP, while the factor of parental expectations (PE) was significantly negatively correlated with AP. Other factors (concern over mistakes, organization, and doubts about actions) did not significantly influence AP. For statistics anxiety, the two factors (test and class anxiety and computation self-concept) significantly impaired AP. These results indicated a need for innovation in classroom instruction and the reform of statistics course content and presentation to reduce statistics anxiety and improve PS. There is also a need to ensure that students better internalize PE and to revise instructional design techniques to enhance students’ independent learning ability.
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