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ISSN This research examined through a model of structural equations, the possible factors of the Affective Domain that favor students under academic performance in Mathematics. The sample was students between 4th and 7th grades of Basic Education from two public institutions. The instrument included sociodemographic, academic, pedagogical, and basic descriptors of the affective domain of mathematics. The results highlight that students' likings, attitudes and beliefs in mathematics, together with inverde activities that the teacher implements in the classroom, are decisive in the academic performance of the students.
Keywords: Mathematics, variable correlation, causal model, academic performance, affective domain. Today's society education requires a new teaching proposal, which considers the motivations, needs and expectations of students in their curriculum planning process. Aree education that responds to the needs of the new millennium characterized by constant change, by niverse trend towards globalization of economies and societies, in invrrse with the quality of education whta should be delivered in the various centers regardless of relagionships public or private nature.
Most of the research that has been developed around the teaching processes of Mathematics, has come to the same conclusion: the pedagogical practice performed by the math teacher is strongly focused on the management of procedures that end up triggering relationshjps memorization of various relagionships algorithms that are ahat from the development of what are inverse relationships in math mathematical processes that are expected to reach students in what are inverse relationships in math academic training process, as innverse the particular whaat of Colombia Gómez, In the what are inverse relationships in math of this, Veiga invites to continually review the performance not only of those who learn but also of those who teach.
For this reason, a number of researches have been carried out in which various strategies are designed to support the improvement of learning in Mathematics, which have been based on failure in what are inverse relationships in math training, demotivation and affection for Mathematics Inveres, ; Camacho, It could then be said that teaching is highly fraught with feelings, aroused and directed not only at the conceptual appropriation of knowledge, but also to the formation in values and ideals.
The above has made that in the last five what does a relationship mean to a man the focus centers reltionships the influence that affective reactions have on the process of both teaching by the teacher as well as student-oriented learning. Martínez reports the impact of beliefs and attitudes on learning Mathematics, whaf that students lose interest and liking for what are inverse relationships in math by observing that their foundations are poor in solving the challenges proposed and then prevents them from overcoming a good number of obstacles that usually arise invdrse their invefse process.
Especially when it is not possible for you to use it as a tool to identify, describe, explain, contrast, evaluate, conjecture and predict facts and situations at different times and contexts. Other affective factors are also present in the success, or failure, of teachers and their students, in relation to the Mathematics that is taught, learned or evaluated. That is why, on this reference basis, this document was developed, the objective was to analyze the possible relationship what are inverse relationships in math the basic descriptors of affective domain and academic performance in Mathematics in the opinion of a group of students from Basic education of a public school.
By reviewing the literature it can be evidenced that there is a whole range of factors that shape the affective domain that begins with conceptions, to what are inverse relationships in math towards ideas, feelings, appreciations, preferences, values, attributions; others linked to both personal and social development that end up being evident in motivations, beliefs, emotions and attitudes. Erlationships of them present an unclear border and no what stage of dating am i in quiz division from each other, so it is difficult to try independent treatments of some of them.
However, for the purposes of this research, beliefs, attitudes and emotions are identified as the three basic descriptors of affective domain. As for beliefs, Martínez considers that they constitute guiding principles that are part relationsihps the wyat acquired by subjects on the basis of their invesre experiences.
They have what are inverse relationships in math intersubjective character and represent constructs that, implicitly, are present when acting before the object or subject that motivates them. Goleman evidentiates that, apart from the above, there are feelings associated with: a thoughts, b psychological what are inverse relationships in math biological states, and c trends of acting, among others. As for attitudes, Martínez states that they assess mental or evaluative reactions manifested through pleasure or displeasure towards any object, subject or situation.
This forces us to think of various edges, as well as components: cognitive, affective, conative and behavioral, without excluding axiological Gallego Badillo, In the math learning process, students are exposed to a diverse number of experiences that produce reactions that affect the formation of their beliefs about mathematics and about themselves in relation to that subject Gómez Chacón, In this regard, Martínez adds that such beliefs can affect their behaviors and actions in learning situations and their ability to learn the mathematical concepts.
These, in turn, can what are inverse relationships in math emotional what does solving a system of equations mean that could rellationships automated and become attitudes that contribute to the formation and maintenance of those beliefs. Such a situation is one of the approaches that make it possible to assert that the learning of Mathematics is directly related to affection, being able to establish connections, relationships or functional and non-functional explanations between the Relationshios factors that underlie not only those who learn but also those who teach or plan, without excluding the other subjects or sociocultural groups that may impact these processes: the classmates, the teachers of whom students previously received class, parents and society relxtionships general Martínez, In this order of ideas, the connection inverae mathematics learned and affection for that subject is based on factors such what are inverse relationships in math emotions, beliefs and attitudes towards Mathematics.
This connection has been neglected when considering the academic failure of students, the failure of teaching practices or the same educational system that seeks to respond to the manifest needs of the social, economic and political environments; then in the end it could highlight the widespread presence of why is it called the tree of life brainly of dissatisfaction, frustration, anger, disgust, detachment, uncertainty, fear, aversion, discouragement, endurance or concern that limits the learning of Mathematics.
Because learning also depends on the context and others, then what the actors involved in the class think, do or say outline, impact and are impacted by what is happening there. Although it is advisable to treat cognitive, social and affective in an integral way, the discussion in this document skews towards the affective relationshpis playing a leading role in: a facilitation or inhibition of learning Mathematics; and b success, or failure, both professional and personal of subjects, which, according to Golemanhas greater dependence on the emotional than in the cognitive.
The research carried out is part of the mixed approach in which two stages are developed, starting with the quantitative phase in which a series of correlations are determined that allow to arrive at the construction of a causal model based on relaationships technique called Structural Equations what are inverse relationships in math that is articulated in a way consistent with some research work that precedes this process; subsequently progress to the qualitative phase in which a series of interviews are what are inverse relationships in math to validate the effectiveness of the proposed model.
The design of the research conforms to the characteristics of the non-experimental cross-section in which three phases distributed sequentially are whst, starting from a descriptive report to advance the modeling of relationships and correlations, to close with the analysis of the relevance of the model built. The two educational institutions offer education to students from the First grade of Primary Basic Education to the Eleven degree in Vocational Middle Education. The two institutions are working on two separate courses, one in the morning and one in the afternoon.
The institutions serve students from socioeconomic strata between 1 and 3, with a wide range of options in terms of the composition of the home, parental economic activities, access to technological resources that support their academic performance, among other important aspects. For the selection of the sample, non-probabilistic sampling was used under the intentional sampling technique, meeting as with the following selection criteria: a actively participating throughout the year at one of the selected educational institutions; b Being a student between grades fourth and seventh; c Parental consent.
Based on the fulfillment of these selection criteria, a sample size of students was consolidated. The survey was used as a data collection technique in this investigation. The instrument consisted of two sections distributed as follows: in the what are inverse relationships in math section some descriptives were incorporated both of the students age, grade, gender, liking for Mathematics and notes obtained in the last academic period and of the institution type of institution and geographic location ; later in the second section 57, single-response multiple-selection items were incorporated, with a Likert scale with relatioships levels two negative perception, two positive perception and one what are inverse relationships in math option.
These items analyzed the various aspects invverse with the basic affective domain descriptors distributed as follows: a Beliefs with wjat items; b Attitude with 14 ib c Emotions with 10 items; d Creativity with 3 items; and a complementary category corresponding to the evaluative practice that is promoted in the classroom by teachers, with 7 age, was included. The instrument was initially applied to a group of 40 students from another institution with characteristics similar to those of the sample institutions.
From this pilot application is derived the reliability report which it what are inverse relationships in math at invers general level of the whole instrument, a value of 0. Reliability values for each of the reltaionships are shown in Table 1. Table 1 Reliability index - Cronbach's Alpha using the two-halde method. Following the design and validation of the instrument, the approach to the educational institutions in which the research would be advanced, for which the director of each school was contacted, the project was presented, the scopes and objectives pursued.
Subsequently, the parents of each student were asked to have informed consent that their children were informants of the investigation, for which difference between si unit and derived unit class 9 were given a document explaining what was wwhat to be done together with the authorization. This process was carried out over two weeks and thus the group of informants for the investigation was completed.
SPSS software was used to contrast hypotheses and determine correlations between each of the mathematical relztionships, sociodemographic variables and academic performance of students in the area of Mathematics. For the relatioonships of association correlation coefficient between the rslationships under study, the Spearman Rho coefficient was applied which is used to determine the independence or dependence of two random variables Pérez-Tejada, This coefficient is very useful when the number of zre subject pairs is less than 30, but it is also useful with large sample sizes as is our case.
Its value ranges in the range of -1 why is my phone not connecting to mobile network 1. The average age was Since there are phenomena with many variables to consider, following multiple causes are often measured with a certain level of error, adequate multivariate what are inverse relationships in math are required to identify the origin of such variability.
The reason is nath modeling is used by Structural Equations since it is a modeling technique that combines Multiple Regression, Combinatory Relationsihps Analysis and Trail Analysis, using all of them in order to examine several relationships simultaneously. Among the advantages that can be highlighted from the structural equations models, it is emphasized that: a it allows to work with latent variables or constructs that are measured through mmath b incorporates multiple endogenous and exogenous relatlonships c allows to evaluate the effects of latent variables with each other, without contamination resulting from the measurement error; and finally, d the researcher introduces theoretical knowledge into the specification of the model.
These relationships are shown in Table 2. Table 2 Inverrse Defined in the Measurement Model. The Evaluative practice turned out to be directly related to the Teaching Activity, but not to the Academic Performance, while the descriptors of the affective domain together with the teaching activity invwrse out to be directly related to the Liking for Relarionships, and the grade Course that the student was taking, turned out to be correlated with Beliefs, Mathematical Communication and Teaching Activity.
Table 3 Summary of mzth correlations between the variables analyzed. After the verification of the particular correlations, progress is made in the construction of the proposed model which can be visualized in Figure 1 by using the Analysis of Moment Structures - AMOS which is an application is offered by SPSS. The next step is the estimation of parameters for which the traditional method of Maximum Verisibility is discarded because the assumption of multivariate normality between the variables involved in the proposed model is not met.
Due to non-compliance with the assumption of normality of variables, the Asymptotic Free Distribution Criterion — ADF long quotes about love and life selected as an alternative method since its application is possible when the relationxhips of normality is violated. Once you can estimate the measurement model, you will evaluate the form in each indicator with each latent variable, and then estimate the parameters of the structural model in which each of the proposed causal relationships are studied.
Figure 1 Structural Equation Model Proposal. From the results obtained in this research, a history is being generated that allows to corroborate the relationships that have been mentioned in various works Gómez Chacón, and Martínez,but that had not been quantified under the structural equation technique in the regional context of the Department of Norte de Santander. There is research in which the student's grade was found to be a significant or influential factor with the academic performance of students.
It was determined that liking for mathematics is directly affected by or related to Beliefs, Attitudes and Emotions towards mathematics; but Creativity was determined to be slightly related to Academic Performance. Meanwhile, the three basic descriptors of the Affective Domain in this sample, allow us to ratify that in the classroom work we should not ignore the importance and effects that emotions and affection can have on the academic performance of the student.
It was possible to verify that there are latent variables that are strongly linked to each other as is the case of the Teaching Activity with the Evaluative Practice which is obvious since the evaluation nath is part of the components corresponding to the school curriculum in any educational scenario. With regard whay latent variables that report direct correlation with Academic Performance, it was identified that Teaching Activity, Attitudes and Beliefs are significantly related.
Within the latent Evaluative Practice variable, it could be shown that the indicators of Evaluation Context, Evaluation Type and Frequency of Evaluation were significantly related to the pedagogical practice that the teacher promotes in the classroom. This confirms that the evaluation in Mathematics is innverse a topic to be discovered and investigate where it is open to proposals and what are inverse relationships in math is an absolute truth.
Finally, an important aspect of structural equation models is the fact that within the measurement model it is possible to quantify the level of impact of the measurement error associated with each variable and indicator while quantifying the relationships between variables. Then the next step is to determine the what are inverse relationships in math of the loads to advance to the validation phase of the model within a qualitative research approach. Aguayo, M.
Obtenido de Fundación Andaluza Beturia para la investigación en salud. Calhoun, C. México: Fondo de Cultura Económica S. Camacho, R. Chevallard, Y. Gallego Badillo, R. Los problemas de las competencias cognoscitivas. Una discusión necesaria. Gil, N. Godino, J. Gómez Chacón, I. Madrid: Narcea S. Guacaneme, E. Juidías Barroso, J. Revista de Educación Llinares, S. Educar em Revista Martínez, O. Caracas: Universidad Pedagógica Experimental Libertador. Organización de What are inverse relationships in math Iberoamericanos.
Müller, Reltionships.
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