Academic Transformation And Motivation In Education Pdf
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- Framework for Information Literacy for Higher Education
- Teaching for Transformation: From Learning Theory to Teaching Strategies
- Academic Transformation
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Framework for Information Literacy for Higher Education
View all 10 Articles. Achievement motivation is not a single construct but rather subsumes a variety of different constructs like ability self-concepts, task values, goals, and achievement motives. The aim of the present study was to investigate whether the reported previous findings can be replicated when ability self-concepts, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria e.
Students self-reported their ability self-concepts, task values, goal orientations, and achievement motives in math, German, and school in general. Additionally, we assessed their intelligence and their current and prior Grade point average and grades in math and German.
Relative weight analyses revealed that domain-specific ability self-concept, motives, task values and learning goals but not performance goals explained a significant amount of variance in grades above all other predictors of which ability self-concept was the strongest predictor.
Results are discussed with respect to their implications for investigating motivational constructs with different theoretical foundation.
Achievement motivation energizes and directs behavior toward achievement and therefore is known to be an important determinant of academic success e. Achievement motivation is not a single construct but rather subsumes a variety of different constructs like motivational beliefs, task values, goals, and achievement motives see Murphy and Alexander, ; Wigfield and Cambria, ; Wigfield et al.
However, a flaw of their study is that they did not assess all motivational constructs at the same level of specificity as the achievement criteria. For example, achievement motives were measured on a domain-general level e. The aim of the present study was to investigate whether the seminal findings by Steinmayr and Spinath will hold when motivational beliefs, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria.
This is an important question with respect to motivation theory and future research in this field. Moreover, based on the findings it might be possible to better judge which kind of motivation should especially be fostered in school to improve achievement. We take a social-cognitive approach to motivation see also Pintrich et al. Social cognitive models of achievement motivation e.
The literature on motivation constructs from these categories is extensive see Wigfield and Cambria, In the following, we describe the motivation constructs in more detail.
Ability self-concepts have been shown to be domain-specific from the early school years on e. Consequently, they are frequently assessed with regard to a certain domain e.
In the present article, task values are defined in the sense of the expectancy-value model by Eccles et al. According to the expectancy-value model there are three task values that should be positively associated with achievement, namely intrinsic values, utility value, and personal importance Eccles and Wigfield, Because task values are domain-specific from the early school years on e.
Performance goals were later further subdivided into performance-approach striving to demonstrate competence and performance-avoidance goals striving to avoid looking incompetent, e.
Some researchers have included work avoidance as another component of achievement goals e. Work avoidance refers to the goal of investing as little effort as possible Kumar and Jagacinski, Goal orientations can be assessed in reference to specific subjects e. McClelland et al. Achievement motives are conceptualized as being relatively stable over time. Consequently, need for achievement is theorized to be domain-general and, thus, usually assessed without referring to a certain domain or situation e.
However, Sparfeldt and Rost demonstrated that operationalizing achievement motives subject-specifically is psychometrically useful and results in better criterion validities compared with a domain-general operationalization.
A myriad of single studies e. For effective educational policy and school reform, it is crucial to obtain robust empirical evidence for whether various motivational constructs can explain variance in school performance over and above intelligence and prior achievement.
Without including the latter constructs, we might overestimate the importance of motivation for achievement. Kriegbaum et al. Steinmayr and Spinath investigated the role of an expectancy component i. Both studies used relative weights analyses to compare the predictive power of all variables simultaneously while taking into account multicollinearity of the predictors Johnson and LeBreton, ; Tonidandel and LeBreton, However, Steinmayr and Spinath who investigated the relations in three different domains did not assess all motivational constructs on the same level of specificity as the achievement criteria.
Thus, the importance of goals and achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match e.
Moreover, we investigated the relations in three different domains: school in general, math, and German. A sample of students was recruited from two German schools attending the highest academic track Gymnasium.
Only 11th graders participated at one school, whereas 11th and 12th graders participated at the other. Students of the different grades and schools did not differ significantly on any of the assessed measures. Students represented the typical population of this type of school in Germany; that is, the majority was Caucasian and came from medium to high socioeconomic status homes.
At the time of testing, students were on average We verify that the study is in accordance with established ethical guidelines. Participation was voluntarily and no deception took place. Before testing, we received written informed consent forms from the students and from the parents of the students who were under the age of 18 on the day of the testing.
All students agreed to participate. Testing took place during regular classes in schools in Tests were administered by trained research assistants and lasted about 2. Students filled in the achievement motivation questionnaires first, and the intelligence test was administered afterward. Before the intelligence test, there was a short break. Table 1. The measure is an adaptation of items used by Eccles and Wigfield in different studies. It assesses intrinsic values, utility, and personal importance with three items each.
Internal consistency of the values scale was high in all domains 0. In accordance with Sparfeldt et al. All items except for the work avoidance items are printed in Spinath and Steinmayr , p. The same was true for performance-approach goals 0. Both subscales were assessed in three domains: school in general, math, and German. The basic module of the test offers assessments of domain-specific intelligence for verbal, numeric, and figural abilities as well as an overall intelligence score a composite of the three facets.
The overall intelligence score is thought to measure reasoning as a higher order factor of intelligence and can be interpreted as a measure of general intelligence, g.
Its construct validity has been demonstrated in several studies Amthauer et al. In the present study, we used the scores that were closest to the domains we investigated: overall intelligence, numerical intelligence, and verbal intelligence see also Steinmayr and Spinath, Raw values could range from 0 to 60 for verbal and numerical intelligence, and from 0 to for overall intelligence.
Internal consistencies of all intelligence scales were high 0. For all students, the school delivered the report cards that the students received 3 months before testing t0 and 4 months after testing t2 , at the end of the term in which testing took place. Grades ranged from 1 to 6, and were recoded so that higher numbers represented better performance. Basically, it uses a variable transformation approach to create a new set of predictors that are orthogonal to one another i. Then, the criterion is regressed on these new orthogonal predictors, and the resulting standardized regression coefficients can be used because they no longer suffer from the deleterious effects of multicollinearity.
These standardized regression weights are then transformed back into the metric of the original predictors. The rescaled relative weight of a predictor can easily be transformed into the percentage of variance that is uniquely explained by this predictor when dividing the relative weight of the specific predictor by the total variance explained by all predictors in the regression model R 2.
We performed the relative weight analyses in three steps. In Model 1, we included the different achievement motivation variables assessed in the respective domain in the analyses. In Model 2, we entered intelligence into the analyses in addition to the achievement motivation variables.
In Model 3, we included prior school performance indicated by grades measured before testing in addition to all of the motivation variables and intelligence. For all three steps, we tested for whether all relative weight factors differed significantly from each other see Johnson, to determine which motivational construct was most important in predicting academic achievement RQ.
Table 1 shows means, standard deviations, and reliabilities. Tables 2 —4 show the correlations between all scales in school in general, in math, and in German. In all three domains i. Table 5 presents the results of the relative weight analyses. In the following, we will describe the results of Model 3 for each domain in more detail. Table 5. Turning to math grades: The findings of the relative weight analyses for the prediction of math grades differed slightly from the prediction of GPA.
We applied sophisticated statistical procedures to investigate the relations in three different domains, namely school in general, math, and German. The relative superiority of ability self-perceptions is in line with the available literature on this topic e. Ability self-concepts showed even higher relative weights than the corresponding intelligence scores. Such a conclusion was supported by the fact that we examined the relative importance of all predictor variables across three domains and at the same levels of specificity, thus maximizing criterion-related validity see Baranik et al.
This procedure represents a particular strength of our study and sets it apart from previous studies in the field e. Alternatively, our findings could be attributed to the sample we investigated at least to some degree. The students examined in the present study were selected for the academic track in Germany, and this makes them rather homogeneous in their cognitive abilities.
It is therefore plausible to assume that the restricted variance in intelligence scores decreased the respective criterion validities. When all variables were assessed at the same level of specificity, the achievement motives hope for success and fear of failure were the second and third best motivational predictors of academic achievement and more important than in the study by Steinmayr and Spinath This result underlines the original conceptualization of achievement motives as broad personal tendencies that energize approach or avoidance behavior across different contexts and situations Elliot, However, the explanatory power of achievement motives was higher in the more specific domains of math and German, thereby also supporting the suggestion made by Sparfeldt and Rost to conceptualize achievement motives more domain-specifically.
Conceptually, achievement motives and ability self-concepts are closely related. Individuals who believe in their ability to succeed often show greater hope for success than fear of failure and vice versa Brunstein and Heckhausen, It is thus not surprising that the two constructs showed similar stability in their relative effects on academic achievement across the three investigated domains.
Teaching for Transformation: From Learning Theory to Teaching Strategies
View larger. The latest research on cognitive theory paired with readable and practical lessons on study skills to create a balanced approach to learning strategies. Academically rigorous yet engaging and practical, Academic Transformation successfully balances cognitive theory and research with realistic and proven skills that readers can deftly apply to their college careers. Utilizing a narrative tone, eye-catching design, and plentiful real-life examples, this text bestows students with life lessons covering the subjects of motivation, procrastination, time management, stress management, and behavior redirection — all while giving readers a solid understanding of why certain strategies lead to goal achievement. The whole approach underscores the importance of self-monitoring and self-regulation. The new second edition has been restructured and revised based on intensive feedback from college and university faculty members across the country that used the first edition text in their classrooms.
Academic transformation: the road to college success / De Sellers, Carol W. Dochen, Russ Hodges.—2nd ed. Dr. De Sellers began one of the earliest cognitive-based learning strategies Psychological Elements that Impact Motivation
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If You're an Educator
Transformative learning is in clear contrast to the more common process of assimilative learning, the type of learning that takes place when students simply acquire new information that can easily fit into their pre-existing knowledge structures. Whereas some college-level courses are aimed at assimilative learning, most courses require at least some level of transformative learning. The posting below looks at the challenges of helping students to make critical paradigm shifts or perspective transformations in their learning. It is by Kelly McGonigal, Ph. Reprinted with permission. No matter what you teach, you face the challenge of bringing students from point A--what they currently know-to point B--the learning goals of a course.
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What steps can colleges and universities take to more effectively support their students? The first in a series examining innovative and effective strategies for improving student success, this introductory article examines current challenges to persistence and completion, and the demographic trends likely to further compound the issues in the coming years. It lays out a framework for building institutions designed to promote student success outcomes. It also surveys some of the most promising innovations across all dimensions of the student experience—from the classroom and support services to campus operations and partnerships with the broader community. Every year across the United States, a significant number of students fail to complete their college degrees. According to the National Student Clearinghouse Research Center, 30 percent of students who entered college in the fall of did not return in the second year. Often saddled with debt, and without the benefit of the increased earning power that college graduates accrue, they tend to face a difficult struggle.