Keywords

University Success, Motivation, Logistics Model.

JEL

I21, I23.

Introduction

The results of our previous work devoted to the analysis of the socio-demographic and initial pathway effects on the internal efficiency of the Faculty of Economics (FSE) of the Université Marien Ngouabi (M'piayi, 2021), revealed inefficiency in student acquisition and success. Although sufficiently related to the educational background and socio-demographic characteristics observed in the study, these results suggested the need to extend the questioning to other variables initially unexplored but likely to provide additional explanations. Doesn't this inefficiency reflect a deeper crisis in the educational system, linked to the loss of confidence and demotivation of students? It is in this spirit that we are taking the initiative to deepen the observation of the same sample of students, on this question of their motivation and their perception of the institution that welcomes them. Indeed, as Vezau & Bouffard (2009) point out, motivation is the essential factor for academic success.

Motivation is understood to be "the set of desires and will that drives a person to accomplish a task or to aim for a goal corresponding to a need" (Legendre, 2005). It is considered a state in which students are generally located at the beginning of the year, ready to walk with the teachers, to apply themselves in the courses, therefore to engage in the educational action (Parent, 2014).

This field of analysis, little explored in the research conducted until recently, as it focused essentially on socio-demographic and socio-economic factors, as well as on initial acquisitions, has become one of the privileged areas of investigation in the educational sciences, as evidenced by the flow of scientific productions. Duguet 2015 citing Delhaxhe, Houart and Pollet, 2011 indicates that learning should not be credited exclusively to the learners. Success is also influenced by the characteristics of the offer.

Thus, in this work, we start from the hypothesis that students' perception of the way the institution functions impacts their success. A negative perception can trigger discouragement, and therefore failure, in students.

Lardy, Bressoux and Lima, 2015 emphasize the value of considering motivational factors in the analysis of the effectiveness of educational institutions, noting the limitations associated with their omission. According to these authors, contrary to what appears in other works such as those carried out by Schmitz et al., (2011), Morlaix & Suchaut (2013) or by Neuville, Frenay, Noël and Wertz, school background alone cannot concentrate the entire explanation of the variance in school success.

Thus, Morlaix & Suchaut (2013) very pertinently integrated this motivational dimension into the analysis of explanatory factors for the success of psychology and economic and social administration (AES) students at the University of Burgundy, controlling for the traditional variables.

This growing awareness among economists and other educational analysts is important because it provides a useful consensus for educational policy.

Taken together, these observations show that motivation is now considered in the research literature to be an important factor in the success of any endeavor. In education, it is rare that all students who enter the educational institution express, at a given moment in their career, the same degree of motivation as before or at the beginning of their training. It may increase or, on the contrary, decline.

It is in this perspective, associated with the set of clusters that suppose a crisis of belief in education in the Congo, that this research is situated. Moreover, to our knowledge, there seems to be no work on this issue in the Congo.

The study is based on a field survey that questioned 205 FSE students about factors that contribute to their motivation or amotivation.

The first section of this article presents the literature review that guides the methodological choices. The second section develops the methodology of the research, presents the specification of the variables and the model, as well as the tests of their robustness. The last section presents the results and their discussion.

Review of The Literature

Theoretical Review

From a theoretical point of view, the notion of motivation refers to various theories, including expectancy-valence theory, achievement goal theory and self-determination theory. The expectancy-valence or value theory, also called expectancy theory (Vroom, 1932), explains the structuring of employee motivation. It indicates that employees are attached to tasks where the chances of achieving the desired results are the highest. However, these results must have a positive value for the individual, such as a salary. It is these expectations that trigger the effort necessary for performance to generate the desired results. In this case, performance is perceived as an instrument, or instrumentality.

The theory of achievement goals (Dweck, 1986; Nicholls, 1984) is in line with Maslow (1943). It evokes the satisfaction that individuals seek, simply by achieving goals. This expected satisfaction is in itself a source of motivation. The goals referred to in this theory refer, on the one hand, to the mastery of new skills (mastery or learning goals) and, on the other hand, to the achievement of performances (performance goals) in the performance of tasks (Carré & Fenouillet, 2009). In both cases, individuals are looking for self-esteem.

A valorizing judgement can favour this satisfaction, the objective achieved being in fact the demonstration of competence (performance approach-goal) or the avoidance of the demonstration of one's incompetence (performance invoidance-goal), which would make it possible to escape an unfavourable judgement (Elliot & Harackiewicz, 1994).

Deci & Ryan's (2000) theory of self - determination, introduced into the analysis of school phenomena by Fortier et al. (1995) sheds some interesting light, particularly in the context of higher education, by distinguishing between students whose motivation is intrinsic, i.e. autonomous, and their colleagues whose motivation is extrinsic. The latter form is considered more effective than the former. Intrinsic motivation is not linked to any form of reward or control Deci (1971), nor to its usefulness for the individual concerned. In this case, it is the pleasure of the activity that is the only source of attraction. This motivation is therefore autonomous. It corresponds to the maximum level of self-determination.

Extrinsic motivation is strategic. It is triggered by the search for reward or the avoidance of punishment and constraint. It is not autonomous in nature and corresponds to a lower level of self determination. Socializing learning is linked to this type of motivation. They can be regulated in 4 different ways external regulation, which corresponds to the intervention of an external actor such as the teacher playing the role of auctioneer by setting rewards or sanctions; introjected regulation, which emphasizes the fact that this "auctioneer" is the individual himself, who would modulate his motivation on the basis of the judgement he would make of himself as a result of the performance that would follow the completion of his activity; identified regulation, which is associated with the performance of an activity without any particular attraction, sometimes against one's will, without having to derive any immediate satisfaction from it, but which aims rather at a defined target; integrated regulation, which evokes the performance of a task on which several other tasks depend.

As for amotivation, this is a construct that suggests the existence of situations that are not triggered by either intrinsic or extrinsic motivation, i.e. individuals who are unable to locate the targets of attraction for their activity for which they have no natural attraction.

Another approach to the analysis of motivation in education, not totally independent of self determination, consists in taking into account the interaction between learners and the actors of education. This approach considers, beyond autonomous motivation which recalls the natural attraction for a given subject and for which a student derives a real and totally disinterested pleasure, and extrinsic motivation, that the student can be influenced by the pedagogical and extra pedagogical context. Indeed, the factors of student motivation are varied. Two main types can be distinguished : those directly related to the educational activity (internal factors) and those that are totally unconnected to it but that act on the accomplishment of the learning task performed by the student (external factors).

These factors are ultimately the ways in which students perceive the overall context of the unfolding of the training process, i.e. the set of events that are imposed on them and their ability to cope with them.

Empirical Review

Studies conducted by Viau et al., (2004) with 4039 undergraduate students show a difference in motivation between first-time students and their colleagues who have been in the program for five years or more. The authors compare different generations, which may suggest a possible generational difference in motivation. However, it is more likely to be a degradation of motivation.

The same authors observed and compared the levels of motivation expressed by students in the faculty of education training future teachers, according to the different learning procedures of the pedagogy. Project-based learning, closer to their future professional concerns, was the most motivating, followed by case studies. Seminars, although highly valued by university teachers, were the least appreciated.

The translation of motivation induced by learners' perceptions of success is tested by Leroy & Bressoux (2010) in a study that targeted 6109 students and 336 teachers. The authors postulate that the motivational climate and the motivational style corresponding to teachers' practices convey signals or representations of various dimensions. These signals are thus interpreted by the learners according to their perception. It is this interpretation that will constitute the motivational environment of the students, whose success measured in the form of a score will be impacted.

This impact is mediated by self- determination and belief in self-efficacy. The results obtained explain nearly 16% of the variance in scores, and even much more (42%) when controlling for student characteristics. We note a negative relationship between the motivational climate and success, which the authors explain by the initial level of acquisition not controlled in the model. The success of good students would in principle be positively affected. The less good ones would be more stressed by the attention teachers show in their practices, thus lowering the level of academic success. Finally, the results validate the existence of an indirect positive effect of the motivational climate on the motivational environment, insofar as it passes through self-determination. This result is similar to that obtained by Mingat (1991) on the analysis of the effectiveness of psycho-pedagogical adaptation groups, whose differentiated, highly attentive pedagogy produces labelling effects that are very harmful to success.

Morlaix & Suchaut (2013) find a positive, but limited, effect of motivation on academic success in research conducted on AES and psychology students, which involves socio-demographic characteristics as control variables. This research shows that motivation weakly improves the explanation of variance and produces a small impact on the success of weaker students. However, it is very beneficial to students in the top quartiles of achievement, particularly median students. The results also provide evidence of an adverse threshold effect on the success of students in the bottom decile, who appear to rely more on their intellectual brilliance and feelings of being competent students. Motivation appears to be mediated by baccalaureate series for socially disadvantaged students.

Ahmed et al., (2018) analyzed the effect of Sudanese students' perceptions about their learning environment, on achievement. Using descriptive statistics and one-way analysis of variance using the Tukey-Kramer test, they find that higher-achieving students expressed a positive perception of the environment.

Similarly, Jones et al., (2021) addressed the effect of students' perceptions of courses, on their success, using structural equation modeling, combined with the qualitative coding method. The results validate the positive effect of course usefulness, which is mediated by course engagement. However, the perception of the ease of the courses reduces the effort in school work, and a perception of difficult courses, costly in learning time, discourages effort and affects success.

The analysis needs to be refined by comparing this literature with the results of econometric modeling.

Methodology

Specification of the Variables

In this study and in accordance with the elements put forward in the literature review, we postulate that the global feeling (SG) expressed by the students of the FSE of the Université Marien Ngouabi, on the quality of the training, triggers motivation or demotivation among them, which is translated by their more or less important commitment towards their academic obligations.

A good appreciation of the pedagogical components should push students to be more assiduous in class and in the library, and to learn the courses more frequently, so as to achieve, in fine, a better level of knowledge acquisition (NAC).

Let NAC = f (SG)    (1)

The explanatory variables that make up the SG vectors result from the dichotomization and are of five (5) types. Each type corresponds to an area subject to the appreciation of the students. These variables characterize the different levels of appreciation expressed by the students in each of the five areas.

Those representing the judgement of the professors' pedagogy correspond to the "very good", "good", "average" or "debatable" assessments (four pedagogical covariates).

The second type of variable represents the levels of assessment of pedagogical monitoring by the course leaders. This follow-up can also be very good, good, average or debatable (four covariates).

The feeling expressed by the students on the reality of the knowledge acquired (feeling of acquiring useful knowledge or not) corresponds to the third type of variables. This feeling can be positive or negative (two covariates).

In addition, the students expressed their perception of the way their institution functions. This functioning can be very good, good, average or questionable.

The last type of explanatory variable concerns the appreciation of the quality of the training, which can be very good, good, average or questionable.

For the variable explained (success), we first constructed the composite variable RL2 defining success in the cycle from the first to the second year of the Bachelor's degree, as follows:

With NLnSm = {1, 2, 3}, the number of semesters spent to validate the semester m (1 or 2) in the level Ln (Licence 1 or 2). Therefore RL₂ = {4, 5, 6, 7, ......}, since it takes at least four (4) semesters to validate an L2 (2 semesters in L1 and 2 semesters in L2).

Then, we distinguished the students who have completed the course without fail, in other words with the minimum of sessions (RL2=4) and those who needed at least one additional session. Hence the following dichotomized definition of REUS success:

If we consider individual i to be a "bad student" or "less good student". And,if one considers that individual i is a "good student"

Specification of the Model

The qualitative nature of the two-modality explained variable leads us to use the logistic model already used in the previous study M'piayi (2021), inspired by the methods of econometric analysis of qualitative variables developed by (Gourieroux, 1989).

The model that allows us to estimate the probability P_i that the individual is a good student (Y=1) will be:

With a: the constant ; b_j : the coefficient associated with the variable X_j whatever the individual i. n : the total number of variables.

The parameters are estimated by maximizing the following associated log-likelihood function:

More precisely, by solving the following system of equations, which follows from the first order conditions of a mathematical function.

J=1,…., n with n, the number of variables.

Presentation of Results and Discussion

We produced two models. The first tests the effects of perception on achievement without any control variables. The second is augmented with the control variables of gender and social background. The results of these models are presented separately, beginning each time, with the exposition of the overall effectiveness tests by means of the ROC (Receiver Operating Characteristic) curve before interpreting the effect of the significant variables reported by the regression.

The ROC curve tests the discriminatory power of the model, i.e. its ability to distinguish between good students (positive values) and bad students (negative values), at each fixed tolerance threshold. This curve is the combination of sensitivity points which define the probability that the model detects the good students, according to the recommended risk of error, and specificity points which concern the less good students. This is the value of the ratio between the total area above the 45° line (bisector) and the area between the ROC curve, which we will call "ROC area". This area measures the level of discriminating power of the model. Indeed, the latter may not have any discriminating power (ROC Area lower than 0.5). Otherwise, this power would be acceptable (ROC Area between 0.5 and 0.7), excellent (ROC Area between 0.7 and 0.9) or exceptional (ROC Area greater than 0.9) figure 1.

The results of the test associated with the first model are presented in graphs 1 and 2 below. They indicate an acceptable discrimination power since the corresponding ROC Area (0.62) is between 0.5 and 0.7 Figure 2.

The results of the model are shown in Table 1 below.

Table 1 Success Explained By Perception Without Control Variables
	Coef.	P- value	Odds ratio	Odds ratio	Odds ratio	Probability
			Value	Lower terminal block	Upper terminal block
Appreciation of teaching pedagogy : very good (Reference)
Good	-0,379	0,305	0,684	0,332	1,411	40,634%
Medium	0,376	0,308	1,457	0,707	3,004	59,300%
Questionable	-0,359	0,392	0,698	0,307	1,589%	41,123%
Appreciation of the follow-up of the organization by the course managers : very good (Reference)
Good	-1,221	0,009	0,295	0,119	0,732	22,778%
Medium	-2,074	0,000	0,126	0,050	0,315	11,169%
Questionable	-2,111	0,000	0,121	0,048	0,308	10,807%
Assessment of the organization of the operation: very good (Reference)
Good	0,545	0,375	1,724	0,518	5,739	63,293%
Medium	-1,087	0,067	0,337	0,925	9,516	25,210%
Questionable	-1,300	0,035	0,272	1,099	12,261	21,413%
Assessment of the quality of the training received: very good (Reference)
Good	0,507	0,225	1,660	0,733	3,760	62,404%
Medium	0,235	0,565	1,265	0,568	2,815	55,847%
Questionable	0,624	0,163	1,866	0,777	4,485	65,114%
Assessment of knowledge acquired: knowledge deemed useful (Reference)
Unperceived usefulness of knowledge	0,058	0,783	1,060	0,699	1,607	51,461%
Constant	-1,007	0,033	0,365	0,145	0,922	26,754%

These results highlight two major facts: the insignificance of the assessment of the teachers' pedagogy, the quality of the training followed and the feeling of usefulness or uselessness of the knowledge acquired (1) and, on the contrary, the significant impact of the assessment of the pedagogical follow-up by the people in charge of the courses and of the organization of the institution's functioning (2).

The marginal effect of the variable X_i on success is calculated as follows:

where Y is the average success rate, approximately 20.3%, and ai is the parameter associated with the variable Xi in the model.

The perception of the pedagogical follow-up seems to be the factor with the greatest impact on success. Students who are very satisfied have, on average, 19.56 points more chance, out of 100, of completing the first two years of the Bachelor's degree in 4 sessions than their colleagues who consider it to be only good. The gap is even greater with each of the other two categories composed of students who consider the pedagogical follow-up to be average or questionable. It amounts to 33.18 and 33.78 points respectively at the 1% threshold. The values of the odds ratios indicate that the chances of being good rather than not so good are 1.36 times higher for students who are very satisfied with the pedagogical follow-up by the course leaders than for those who judge it as simply good, but with a 23% probability. They are 3.17 times more likely to be in the reference category than among students who rate it as average, with a probability of 11%. Those who find it questionable are 3.25 times less likely to be good students rather than not so good than their very satisfied colleagues, with a fairly low probability of 10%. These values indicate a real inequality in the students' chances of success, linked to the difference in their perception insofar as, being different from unity, the Indicator expresses structural inequality.

Estimators for the assessment of the organization of the FSE operation indicate that "very good" and "good" judgments do not significantly differ in terms of chances of success. On the other hand, there is a mean difference of 17.4 points at the 10% threshold and 20.8 points at the 5% threshold between students who are very satisfied and those who consider it just average or questionable respectively, more favorable to the reference category. The chances of being a good student rather than a not so good one are 1.76 and 1.29 times lower among students who appreciate the organization of the institution's functioning moderately or questionably than among those who are very satisfied with it, with 25, 21 and 21.41% chances respectively. As in the case of the sensitivity of the appreciation of the pedagogical follow-up, the discriminating effect of the appreciation of the organization of the institution's functioning on student success is significantly established.

These econometric results confirm the link between success and the perception of the organization of operations, observed in the statistical analysis conducted in the second section. On the other hand, the link between success and the degree of appreciation expressed in the other areas observed appeared insignificant in the econometric analysis. We can assume, as Duguet 2015 indicates, the possibility that the effect of these factors is absorbed by some variables not taken into account in the modeling. Thus, we find it useful to develop a second model that introduces some control variables figure 3.

The overall efficiency tests (ROC Curve) of the augmented model are shown in Graphs 3 and 4 below. The introduction of the control variables improves the ROC Area from 0.6205 to 0.6785. The model thus presents an acceptable discriminating power figure 4.

The Estimators Revealed by the Augmented Model are Shown in Table 2 Below

Table 2 Success Rate Explained By Student Perception Controlling For Social Origin And Gender
	Coef.	P. value	Odds ratio	Probability
Gender : Male (Reference)
Female	-0,517	0,000	0,596	37,358%
Father's CSP : executive and higher intellectual profession (Reference)
Craftsman, merchant, company manager and self-employed	0,105	0,579	1,111	52,624%
Intermediate profession	-0,336	0,476	0,715	41,684%
Employee or worker	-0,647	0,000	0,524	34,377%
Unemployed	-0,825	0,014	0,438	30,471%
Assessment of teaching methods : very good (Reference)
Good	-0,444	0,276	0,641	39,079%
Medium	0,485	0,241	1,625	61,900%
Debatable	-0,347	0,434	0,707	41,416%
Assessment of the pedagogical follow-up by the course leaders: very good (Reference)
Good	-1,187	0,014	0,305	23,378%
Medium	-2,311	0,000	0,099	9,025%
Debatable	-2,317	0,000	0,099	8,971%
Assessment of the organization of the operation : very good (Reference)
Good	0,493	0,443	1,638	62,089%
Medium	0,987	0,113	2,683	72,851%
Debatable	-1,309	0,043	0,270	21,271%
Assessment of the quality of the training received : very good (Reference)
Good	0,819	0,153	2,269	69,411%
Medium	0,549	0,194	1,731	63,389%
Debatable	-0,970	0,035	0,379	27,491%
Assessment of knowledge acquired: knowledge deemed useful (Reference)
Unperceived usefulness of knowledge	0,193	0,370	1,213	54, 807%
Constant	-0,144	0,794	0,866	46,414%

The results in this table 2 show that, controlling for gender and social origin, the effect of pedagogical follow-up and the organization of the training remains. The impact of the judgment of the quality of the training becomes significant. We note the absence of a significant effect of the perception of the teachers' pedagogy and the usefulness of the knowledge acquired. The two control variables are significantly influential.

If we take the very satisfied students as the reference category, the difference in the chances of success with those who judged the pedagogical follow-up by the course leaders as good, average and questionable, is respectively 19, 37 and 37 points out of 100, more favourable to this reference category, at the respective thresholds of 5%, 1% and 1%. These marginal effects seem to be slightly larger than those of the previous model. Thus, the chances of being a good student rather than a not so good one are 10 times higher for students who have a very positive perception of the pedagogical follow-up than for those who express a questionable or average opinion. These chances are only 3.3 times greater for those students who are very satisfied than for their colleagues who rate it as average.

A comparison between students who are very satisfied with the quality of the training and those who find it questionable shows that the chances of being good rather than less good are 2.6 times greater in the former category than in the latter. Similarly, a good assessment of the organization of the operation multiplies by 3.7 the chances of being a good student instead of a less good one, compared to those who consider it questionable.

With regard to the control variables, we find the significant effect of social origin already mentioned in previous studies (M'piayi, 2021). Students from a working class social background (unemployed, blue collar or white collar fathers) have more difficulties in achieving success than other categories, in this case students whose fathers are executives or professionals. The latter, for example, have 13.2 and 10.35 points more chances of success than their colleagues with unemployed, blue collar or working class fathers respectively. Thus, the odds of being a good student instead of a not so good one are 2.28 and 1.9 times higher for students with executive, professional, and higher education fathers than for their colleagues with unemployed and blue collar fathers, respectively.

The effect of gender, which was not significant in the previous analysis, turns out to be highly significant at the 1% threshold. Girls do less well than boys. The difference in the chances of success between the two categories is 8 points out of 100. The odds ratio indicates that the odds of success instead of failure are 1.11 times higher for boys than for girls. Thus, there is a fluidity that characterizes equity between girls and boys. The differences in chances of success would not be explained by the retention force that each category would exert on its subjects.

However, some limitations must be taken into account when interpreting these results. These are the possible hidden variables whose perception would mediate their effect on success, or which, on the contrary, would mediate the impact of perception. In addition, the importance and the stakes of this research could have required the observation of a larger population, in order to give more credibility to the results.

Conclusion

This article focused on the impact of the perception expressed by third year Bachelor's and Master's I and II students at the FSE of the Université Marien Ngouabi. Assuming that the students' feelings were likely to trigger motivation or demotivation in the fulfillment of their academic obligations, we collected their judgments on the pedagogy of the teachers, the pedagogical follow up of those in charge of the courses, the overall quality of the training, the organization of the functioning and the usefulness of the acquired knowledge. The statistical cross tabulations and the logistic modelling validate the existence of a significant impact of the perception of the pedagogical follow up, of the organization of the training, and even of the quality of the training under the control of age and social origin, on the fluidity in the course at the level of the first two years of the licence. The strength of the negative illustrations collected during the survey leads us to suggest that decision makers should make innovations in the follow up of students and in the organization of the institution's operations. We recall, for example, the tutoring provided by students under the responsibility of course leaders, seminars on pedagogical and scientific themes in the university environment to reinforce the skills of the teaching staff, socially differentiated student aid to take into account social inequalities in the face of academic success, an effort to modernize equipment and teaching materials, all of which was punctuated by the installation of a joint management cell for student grievances and corruption issues. These results show the need for a study with a larger and more varied sample that would allow the foundations of the recommendations to be consolidated. It would be appropriate, for example, to measure the level of student engagement and the tone of success.

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Received: 23-Dec-2022, Manuscript No. JEEER-22-13035; Editor assigned: 26-Dec-2022, Pre QC No. JEEER-22-13035(PQ); Reviewed: 11-Jan-2023, QC No.JEEER-22-13035; Revised: 13-Jan-2023, Manuscript No. JEEER-22-13035(R); Published: 27-Jan-2023