In this study we investigate how prior knowledge, the comprehensive learning approach, problembased teaching and assessment influence students’ basiclearning skills in Mathematics at the university level. To do so, we employed a quasiexperimental research design and a structured questionnaire. Two experimental groups and two control groups of students were involved. We found a negligible correlation between prior knowledge and basiclearning skills but a positive correlation between prior knowledge and the comprehensive learning approach. On the other hand, we found practically no correlation between prior knowledge and assessment. We also found that problembased teaching correlated positively and that the traditional approach correlated negatively with prior knowledge. Moreover, prior knowledge, problembased teaching, the comprehensive learning approach and assessment explained 50% of the variance in the levels of basiclearning skills.
El objeto de este estudio es investigar la influencia del conocimiento previo del alumnado, el enfoque de aprendizaje integral, la enseñanza basada en problemas y el impacto de la evaluación en el aprendizaje básico del estudiante de matemáticas a nivel universitario. La investigación plantea un diseño de investigación cuasi experimental y un cuestionario estructurado. En él participaron dos grupos experimentales y dos grupos de control. Los resultados muestran que existe una correlación no significativa entre el conocimiento previo y la habilidad de aprendizaje básico; también plantea que un enfoque de aprendizaje integral se correlaciona positivamente con el conocimiento previo, mientras que con la evaluación casi no existe correlación, si bien existe una correlación positiva con la enseñanza basada en problemas. El enfoque tradicional se correlaciona negativamente con el conocimiento previo. Otros resultados que se obtienen es que el conocimiento previo, la enseñanza basada en problemas, el enfoque de aprendizaje integral y el impacto de la evaluación explican el 50% de la variación en los niveles de habilidades de aprendizaje básico.
El propòsit d'aquest estudi és investigar la influència del coneixement previ de l'alumnat, l'enfocament d'aprenentatge integral, l'ensenyament basat en problemes i l'impacte de l'avaluació en l'aprenentatge bàsic de l'estudiant de matemàtiques a nivell universitari. La investigació planteja un disseny quasiexperimental i un qüestionari estructurat. Hi van participar dos grups experimentals i dos grups de control. Els resultats mostren que hi ha una correlació no significativa entre el coneixement previ i l'habilitat d'aprenentatge bàsic. L'estudi també va revelar que un enfocament d'aprenentatge integral es correlaciona positivament amb el coneixement previ, mentre que amb l'avaluació gairebé no hi ha correlació. D’altra banda, s'observa que hi ha correlació positiva amb l'ensenyament basat en problemes. L'enfocament tradicional es correlaciona negativament amb el coneixement previ. La investigació també planteja que el coneixement previ, l'ensenyament basat en problemes, l'enfocament d'aprenentatge integral i l'impacte de l'avaluació expliquen el 50% de la variació en els nivells d'habilitats d'aprenentatge bàsic.
Mathematics proficiency has always been a challenge for lecturers and students at university. Many researchers have investigated the factors related to students’ achievements in mathematics, such as mathematics preferences, teachers’ knowledge and teacher’s behavior, as well as students’ thinking and learning, and cognitive complexity.
The researcher examined and revealed that a comprehensive learning approach correlates positively with knowledge conceived, as well as half of the variance of basiclearning skill levels is explained by prior knowledge, problembased teaching, comprehensive learning approach, and assessment impact. The researcher also found that problem based teaching is making a significant positive contribution, meanwhile, the traditional approach is making a significant but negative contribution to the prediction of basiclearning skill.
While students’ achievements in mathematics has proven to be the most challenging experience for students, as well as the lecturers, mathematics departments might pretest prior knowledge of students to strengthen their work to increase their academic success in mathematics, as well as might promote the comprehensive learning approach, and. problembased teaching. There is a need to investigate the influence of other variables on basiclearning skill in mathematics.
The prior mathematics knowledge, comprehension learning approach, as well as problembased teaching used by teacher and assessment impact, are supposed to be the important variables that influence knowledge conceived in mathematics. The main aim of the study was to investigate the impact of prior knowledge, comprehensive learning approach, problembased teaching and assessment impact on student's basiclearning skill in mathematics. Learning is to be student‐initiated and that ample time for self‐study should be available (
The fundamental factors in the educative process are an immature, undeveloped being; and certain social aims, meanings, values incarnate in the matured experience of the adult. The educative process is the due interaction of these forces. Abandon the notion of subject matter as something fixed and readymade in itself, outside due child's experience; cease thinking of the child’s experience as also something hard and fast; see it as something fluent, embryonic, vital; and we realize that the child and the curriculum are simply two limits which define a single process. The present standpoint of the child and the facts and truths of studies define instruction (
Constructivism is grounded in the concept that learners construct their understanding through experiences and interpretations (
Prior mathematical knowledge in secondary education is thought to be one of the most important premises to obtain good grades in mathematics in the university studies. Many authors have done a lot of research to investigate the association between prior knowledge in mathematics and basiclearning skill in university studies.
Prior knowledge had a positive influence on new learning (
The comprehensive learning approach is assumed to be one of the important variables that impact basiclearning skill in mathematics at the university. A lot of research is carried out to investigate the association between comprehensive learning approach in mathematics and basiclearning skill at university. (
Problembased teaching used by math teachers is supposed to be one of the most important variables that impact basiclearning skill in mathematics. A lot of research has been done to investigate the association between problembased teaching in mathematics and basiclearning skill at university.
Collaborative problemsolving performance is positively related to performance in the core PISA subjects (science, reading and mathematics), but the relationship is weaker than that observed among those other domains (
(
Knowledge assessment of students is one of the important variables that are related to basiclearning skill in mathematics. A lot of research is carried out to investigate the association between assessment impact in mathematics and basiclearning skill in the university studies.
Assessment methods and matriculation examination score were the predictors of students’ progress (
Assessment support the advancement of teaching and learning (
Many researchers have done a lot of work to investigate the impact of prior knowledge, comprehensive learning approach, problembased teaching, and assessment impact on basiclearning skill in mathematics. Approaches to instruction and curriculum design, formative assessment data and feedback to students (
The quantitative approach was the method used in the research. A quasiexperimental research design was used. Quasiexperimental designs do not include the use of random assignment. Researchers who employ these designs rely instead on other techniques to control, or at least reduce threats to internal validity (
In the quasiexperimental research design, the matchingonly design was used in the study. The matchingonly design differs from random assignment with matching only in the fact that random assignment is not used. The researcher still matches the subjects in the experimental and control groups on certain variables, but he has no assurance that they are equivalent on others. When several groups are available for a method study and the groups can be randomly assigned to different treatments, this design offers an alternative to random assignment of subjects. After the groups have been randomly assigned to the different treatments, the individuals receiving one treatment are matched with individuals receiving the other treatments (
Teaching method was selected to be used as a manipulated variable: traditional vs problem based teaching, controlling the moderator, mediator and extraneous variables: teaching, curriculum, climate, class management, and technology as a teaching tool.
Two experimental and two control groups of freshman and sophomore students as a nonrandom sample were selected to be investigated in the research. The two experimental groups of students: finance bank, business administration (N=135) were selected in the economic faculty of the university. Meanwhile, the two control groups of students: economical informatics, and information technology (N= 121) were selected in information technology and innovation faculty of the university. The four groups of respondents, except the fact that are from different faculties, they were taught the same syllabus of mathematics curriculum. Relating to classification at university, 81 respondents from experimental groups (60%) were freshman, and 54 respondents (40%) were the sophomore students. Meanwhile, 56 respondents from control groups (46.3%) were freshman, and 65 respondents (53.7%) were the sophomore students. Two experimental groups sample of respondents is composed by 18 females (13.3%), and 117 (86.7%) males; meanwhile two control groups sample of respondents is composed by 32 females (26.4%), and 89 (73.6%) males. Relating to the choice of career, 90 respondents (66.7%) from experimental groups studied in the first choice, 27 (20%) in the second choice, 9 respondents (6.7%) in the third choice, and 9 respondents (6.7%) in the fourth choice. Meanwhile, 40 respondents (33.1%) from control groups studied in the first choice, 32 (26.4%) in the second choice, 24 respondents (19.8%) in the third choice, and 25 respondents (20.7%) in the fourth choice.
A structured questionnaire was used to gather the primary data from the students in the 2018 2019 academic year. The questionnaire is based on CEVEAPEU questionnaire an instrument to assess the learning strategies of university students (
Alfa Cronbach values of questionnaire scales vary from .83 to .91 confirming a very good value of reliability, as following
N0 
Variables 

Evaluation 

1 
Prior knowledge 
.89 
Good 
2 
Comprehensive learning approach 
.91 
Excellent 
3 
Problembased teaching 
.88 
Good 
4 
Assessment impact 
.85 
Good 
5 
Basiclearning skill 
.83 
Good 
Central tendency values, as well as frequency values, were used to describe the prior mathematics knowledge, comprehensive learning approach, problembased teaching, assessment impact, and knowledge conceived in mathematics for both, experimental and control groups. Pearson productmoment correlation coefficient was used to assess the relationship between prior mathematics knowledge, comprehensive learning approach, problembased teaching, assessment impact, and knowledge conceived in mathematics. Linear multivariate regression was used to assess the ability of one control measure to predict knowledge conceived in mathematics by prior knowledge, comprehensive learning approach, problembased teaching, and assessment impact. Preliminary assumption testing was conducted to check for normality, linearity, outliers, homogeneity of variancecovariance matrices, and multicollinearity, with no violations noted.
Frequencies and central tendency values of prior knowledge, comprehensive learning approach, problembased teaching, assessment impact, and basiclearning skill variables for experimental and control group of respondents are shown below. The statistical tables with frequencies and central tendency values of main variables are shown in the annexes. The more detailed frequencies of main variables according to gender and study program as crosstabs tables are shown in the annexes too.
Prior knowledge’ frequencies indicates that most of the respondents (46.7%) of the experimental groups and 40.5% of the control groups passed in the previous academic year; 33.3% of the experimental groups and 39.7% of the control groups achieved good results; meanwhile 20% of the experimental groups and 19.8% of the control groups achieved high results. Central tendency values for experimental groups (M= 2.733, SD = .774), as well as for control groups (M= 4.00, SD = .897), indicate the same tendency for values as measured by frequencies. Hence, there are small differences of prior knowledge (pass: 6.2%; good: 6.4%; high: 0.2%) between the experimental and control groups of students. Therefore, there are small differences of prior knowledge between the experimental and control groups of students.
Comparing prior knowledge from previous academic year with current knowledge of experimental group has resulted that: (1) 5.93 % more students fail; (2) 2.96% more students pass, (3) 4.44% less students achieved good; (4) 4.44% less students achieved outstanding results in mathematics. Comparing prior knowledge from previous academic year with current knowledge of control group scores has shown that: (1) 9.09 % more students fail; (2) 6.61% more students pass, (3) 8.27% less students achieved good; (4) 7.43% less students achieved outstanding results. Hence, there is a difference between experimental and control group of students, especially in fail and outstanding levels achieved in mathematics.
Comprehensive learning approach’ frequencies indicates that most of the respondents (53.4%) of experimental groups and 47.1% of control groups include full information from class reading material, practical, etc. during learning; 13.3% of the experimental groups and 26.4% of the control groups include a little; meanwhile 33.3% of the experimental groups and 26.4% of the control groups are undecided. Central tendency values for experimental groups (M= 3.46, SD = .808), as well as for control groups (M= 2.79, SD = .751) indicate the same tendency for values as measured by frequencies. Therefore, there are small differences of comprehensive learning approach (fully include: 6.3%; a little include: 13.1%; undecided: 6.9%) between the experimental and control groups of students.
Problembased teaching’ frequencies indicates that most of the respondents (66.7%) of the experimental groups and 19.8% of control groups have acquired fully support by lecturers in every lesson during teaching; 6.7% of the experimental groups, and 60.4% of the control groups a little support; meanwhile 26.7% of the experimental groups and 19.8% of the control groups are undecided. Central tendency values for experimental groups (M= 3.86, SD = .887), as well as for control groups (M= 3.27, SD = .930), indicate the same tendency for values as measured by frequencies. Hence, there are substantial differences of problembased teaching (fully support: 46.9%; a little support: 53.7%; undecided: 6.9%) between the students to whom problembased teaching is used compared to the students to whom the traditional approach is used.
Assessment impact’ frequencies indicates that most of the respondents (73.3%) of experimental groups and 66.9% of control groups have fully learned from mistakes and study better next time if they don’t do well in an exam; 6.7% of the experimental groups and 6.6% of the control groups have a little learning; meanwhile 20.0% of the experimental groups and 26.4% of the control groups are undecided. Central tendency values for experimental groups (M= 2.73, SD = .774), as well as for control groups (M= 3.40, SD = 1.311), indicate the same tendency for values as measured by frequencies. Therefore, there are small differences of assessment impact (fully learned: 6.4%; a little learned: 0.1%; undecided: 6.4%) between the experimental and control groups of students.
Basiclearning skill’ frequencies indicates that most of the respondents (53.4%) of experimental groups and 53.7% of control groups are fully able to learn the basic concepts taught in the math course; 6.7% of the experimental groups and 6.6% of the control groups are a little able; meanwhile 26.7% of the experimental groups and 26.4% of the control groups are undecided. Central tendency values for experimental groups (M= 4.00, SD = .897), as well as for control groups (M= 3.80, SD = .832), indicate the same tendency for values as measured by frequencies. Hence, there are small differences of basiclearning skill (fully able: 0.3%; a little able: 0.1%; undecided: 0.3%) between the students to whom problembased teaching is used compared to the students to whom the traditional approach is used.

Basiclearning skill 
Prior knowledge 
Comprehensive learning approach 
Problembased teaching 
Assessment impact 

Basiclearning skill 
1.000 
.008 
.417 
.319 
.029 
Prior knowledge 
.008 
1.000 



Comprehensive learning approach 
.417 

1.000 


Problembased teaching 
.319 


1.000 

Assessment impact 
.029 



1.000 

Basiclearning skill 
Prior knowledge 
Comprehensive learning approach 
Problembased teaching 
Assessment impact 

Basiclearning skill 
1.000 
.003 
.443 
.048 
.106 
Prior knowledge 
.003 
1.000 



Comprehensive learning approach 
.443 

1.000 


Problembased teaching 
.048 


1.000 

Assessment impact 
.106 



1.000 
H # 1: As shown in
H # 2: As shown in
H # 3: As shown in
H # 4: As shown in
Model Summary 


Experimental groups^{b} 






Change Statistics 


Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
R Square Change 
F Change 
df1 
df2 
Sig. F Change 
DurbinWatson 
1 
.713^{a} 
.508 
.493 
.93370 
.508 
33.570 
4 
130 
.000 
1.802 
Control groups^{b} 






Change Statistics 


Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
R Square Change 
F Change 
df1 
df2 
Sig. F Change 
DurbinWatson 
1 
.748^{a} 
.559 
.544 
.79902 
.559 
36.786 
4 
116 
.000 
1.768 
H # 5: As shown in
Coefficients Experimental Groups 





Model 1 

Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 
95% Confidence Interval for B 
Correlations 
Collinearity Statistics 


B 
Std.Error 
Beta 
Lower Bound 
Upper Bound 
Zeroorder 
Partial 
Part 
Tolerance 
VIF 


(Constant) 
1.016 
.544 

1.869 
.064 
.060 
2.092 






Prior Knowledge 
.261 
.107 
.154 
2.430 
.006 
.473 
.048 
.093 
.208 
.149 
.943 
1.061 

Comprehensive learning approach 
1.067 
.162 
.658 
6.571 
.000 
.746 
1.389 
.646 
.499 
.404 
.377 
2.651 

Problembased teaching 
320 
.136 
.217 
2.351 
.002 
.051 
.590 
.565 
.202 
.145 
.445 
2.246 

Assessment impact 
.460 
.111 
.315 
4.153 
.000 
.680 
.241 
.171 
.342 
 
.657 
1.523 


Model 1 

Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 
95.0% Confidence Interval for B 
Correlations 
Collinearity Statistics 


B 
Std.Error 
Beta 
Lower Bound 
Upper Bound 
Zeroorder 
Partial 
Part 
Tolerance 
VIF 


(Constant) 
.150 
.478 

.313 
.755 
1.097 
.798 






Prior Knowledge 
.181 
.098 
.115 
1.852 
.006 
.013 
.375 
.055 
.169 
.114 
.982 
1.018 

Comprehensive learning approach 
.800 
.083 
.629 
9.640 
.000 
.635 
.964 
.666 
.667 
.594 
.892 
1.121 

Traditional approach 
.314 
.062 
.320 
5.047 
.000 
.437 
.191 
.221 
.424 
.311 
.943 
1.060 

Assessment impact 
.276 
.095 
.194 
2.909 
.004 
.088 
.464 
.326 
.261 
.179 
.852 
1.174 
For experimental groups, beta value for prior knowledge is.154, for comprehensive learning approach, is .658, for problembased teaching is .217, and for assessment impact is .315. The largest beta standardized coefficient is .658, which is for comprehensive learning approach.
For control groups, beta value for prior knowledge is.115, for comprehensive learning approach is .629, for the traditional approach is .320, for assessment impact, is .194. The largest beta standardized coefficient is .629, which is for comprehensive learning approach.
According to frequencies as well as the central tendency values, there are small differences of prior knowledge between the experimental and control groups of students. Thus, the students to whom the problembasedlearning approach is used reported higher levels of prior knowledge compared to the students to whom the traditional approach is used. Comparing prior knowledge from previous academic year with current knowledge scores it is found that there is a difference between experimental and control group of students, especially in fail and outstanding levels achieved in mathematics. Therefore, faculties, as well as mathematics departments might pretest prior knowledge of students to strengthen their work to increase their academic success in mathematics.
Frequencies as well as the central tendency values indicate that there are small differences of comprehensive learning approach between the students to whom problembasedlearning approach is used compared to the students to whom traditional approach is used. Hence, faculties, as well as mathematics departments might promote the comprehensive learning approach.
Frequencies as well as the central tendency values indicate that there are bigger differences of problembased teaching between or the students to whom problembasedlearning approach is used compared to the students to whom traditional approach is used. Hence, faculties, as well as mathematics departments might promote and use more problembased teaching.
According to frequencies as well as the central tendency values there are small differences of assessment impact between the students to whom problembasedlearning approach is used, compared to the students to whom the traditional approach is used.
Therefore, faculties, as well as mathematics departments might use assessment to increase its impact on students' learning to learn from mistakes and study better next time if they don't do well in an exam.
Frequencies, as well as the central tendency values, indicate that there are small differences of basiclearning skill between the students to whom problembasedlearning approach is used, compared to the students to whom traditional approach is used. Hence, faculties, as well as mathematics departments might support the students to be able to learn the basic concepts taught in the math course.
Pearson correlation outputs indicate that there is a negligible correlation between prior knowledge and basiclearning skill variables (r^{2} = .008) for experimental groups as well as for control groups (r^{2} = .003). Furthermore, there is not a statistically significant relationship between prior knowledge and basiclearning skill by students, thus a random chance could explain the result. The value of correlation indicates that other variables might be important in variance prediction of basiclearning skill scores. So, future researchers may do more work to investigate the influence of other variables on basiclearning skill. The result was not consistent with some previously reported works, who argued that prior knowledge influence basiclearning skill scores (
Pearson correlation outputs indicate that there is a significant positive correlation between comprehensive learning approach and basiclearning skill variables (r^{2} = .417) for the experimental groups as well as for control groups (r^{2} = .443). Therefore, high scores of comprehensive learning approach are associated with high scores of basiclearning skill. The value of r^{2} indicates that other variables might be important in variance prediction of basiclearning skill scores. So, future researchers may do more research to investigate the influence of other variables on basiclearning skill. The result was consistent with some previously reported works, who argued that comprehensive learning approach influence basiclearning skill scores (
Pearson correlation outputs indicate that there is a significant positive correlation between problembased teaching and basiclearning skill variables (r^{2} = .319) for the experimental groups, meanwhile, there is a low negative correlation between traditional approach and basiclearning skill for the control groups (r^{2} = .048). Hence, high scores of problembased learning teaching’ strategies are associated with high scores of basiclearning skill. Meanwhile, high scores of traditional teaching are associated with low scores of basiclearning skill. The value of correlation indicates that other variables might be important in variance prediction of basiclearning skill scores. So, future researchers may do more work to investigate the influence of other variables on basiclearning skill. The result was consistent with some previously reported works, who argued that problembased teaching influence basiclearning skill scores (
Pearson correlation outputs indicate that there is a negligible correlation between assessment impact and basiclearning skill variables (r^{2}= .029) for the experimental groups as well as for control groups (r^{2} = .106). Therefore, it is expected that the scores of assessment impact are not associated with thw scores of basiclearning skill. The value of r^{2} indicates that other variables might be important in variance prediction of basiclearning skill scores. So, future researchers may do more research to investigate the influence of other variables on basiclearning skill. The result was not consistent with some previously reported works, who argued that assessment impact influence basiclearning skill scores (
Regression outputs indicate that the total variance of basiclearning skill levels explained by prior knowledge, problembased teaching, comprehensive learning approach and assessment impact (the model) is 50.8% for the experimental groups and 54.4% for the control groups. The model reaches statistical significance (Sig. = .000).
Problembased teaching beta value in the experimental groups means that 21.7% of the variance on basiclearning skill is explained by problembased teaching. Hence, problem based learning or manipulated variable is making a significant contribution to the prediction of basiclearning skill dependent variable in the experimental groups.
Traditional approach beta value in the control groups is negative and means that 32.0% of the variance on basiclearning skill dependent variable is explained by the traditional approach. Therefore, traditional teaching independent non manipulated variable is making a significant but negative contribution to the prediction of the basiclearning skill dependent variable in the control groups.
Meanwhile, beta values for prior knowledge and assessment impact in the experimental groups are negatives and are explained 15.4% and 31.5% of the variance on the dependent variable. The largest beta standardized coefficient is .658, which is for comprehensive learning approach. This means that this variable makes the strongest unique contribution to explaining the dependent variable.
Beta value in the control groups for prior knowledge explain 11.5%, and beta value for assessment impact is negative and explain 19.4% of the variance on the dependent variable. The largest beta standardized coefficient is .629, which is for comprehensive learning approach. This means that this variable makes the strongest unique contribution to explaining the dependent variable.
Therefore, problem based teaching is making a significant positive contribution, meanwhile, the traditional approach is making a significant but negative contribution to the prediction of basiclearning skill. The result was consistent with some previously reported works, who argued that higher prior knowledge, comprehensive learning approach, problembased teaching, and higher assessment impact scores predict higher basiclearning skill scores (
The results of this study supported by other researchers about the basiclearning skill in mathematics have important implications for future research on academic achievements. Such research should investigate various variables and their relation to basiclearning skill. Results of this study about basiclearning skill also have important implications for practice. The important programs or other interventions should be designed to develop and to support students to obtain better results in mathematics.
Several limitations of the study should be acknowledged as part of the conclusion. First, the measurement of prior knowledge, comprehensive learning approach, problembased teaching, assessment impact, and basiclearning skill variables is made through using of self reported instrument. Second, the study included four independent variables, since it is known that basiclearning skill is influenced by other variables as well. The prior assumption was that prior knowledge, comprehensive learning approach, problembased teaching, and assessment impact student's basiclearning skill.
The results showed that there are small differences of prior knowledge between the students to whom the problembased teaching approach is used compared to the students to whom the traditional approach is used. The study confirmed that there are small differences of comprehensive learning approach and assessment impact between the students to whom the problembased teaching approach is used compared to the students to whom the traditional approach is used. The results showed that there are substantial differences of problembased teaching between the students to whom problembased teaching is used compared to the students to whom the traditional approach is used. The results showed that there are small differences of basiclearning skill between the students to whom problembased teaching is used compared to the students to whom the traditional approach is used.
It is found that there is a negligible correlation between prior knowledge and basiclearning skill, and there is not a statistically significant relationship between them. It is found that a comprehensive learning approach correlate positively with knowledge conceived, meanwhile, assessment almost does not correlate. Thus, higher scores of learning approach are associated with higher scores of basiclearning skill. It is found that problembased teaching correlates positively with basiclearning skill, meanwhile traditional approach correlates negatively with basiclearning skill Thus, higher scores of problembased teaching are associated with high scores of basiclearning skill, meanwhile higher scores of traditional approach are associated with lower scores of basiclearning skill.
The study found that 50% of the variance of basiclearning skill levels is explained by prior knowledge, problembased teaching, comprehensive learning approach, and assessment impact. It is found that problembased teaching explains 21.7% of the variance of basiclearning skill, prior knowledge 15.4%, comprehensive learning approach 65.8%, and assessment impact 31.5%. The other variance may be explained by hidden or unknown variables. The study confirmed that the comprehensive learning approach makes the strongest unique contribution to explaining basiclearning skill in mathematics. Problembased teaching is making a significant positive contribution, meanwhile, the traditional approach is making a significant but negative contribution to the prediction of basiclearning skill in mathematics.
https://zenodo.org/record/4244124#.X6voxchKiM8