The question of how learners’ motivation influences their academic achievement and vice versa has been the subject of intensive research due to its theoretical relevance and important implications for the field of education. This study shows how influential theories of academic motivation have conceptualized reciprocal interactions between motivation and achievement, and the kinds of evidence that support this reciprocity.
Mediating Factors Between Motivation and Achievement
Motivation and emotion can be a difficult line to draw. Both of these concepts can interact, although emotions are depicted as more temporary than motivation. For instance, certain emotions can either enhance or obstruct motivation. Just like how there have been studies on the relationship between motivation and student achievement, there are recent studies on the reciprocal relationship between emotions and student achievement.
There are several mediating factors between motivation and achievement. When effort is measured as quality of learning (e.g., selecting adaptive goals, adopting higher-quality learning strategies, etc.), there is some evidence for a positive link between academic achievement and effort. However, when effort is measured as a quantity of learning (such as study time, practice time, time-on-task, persistence, etc.), this relationship seems either weak or only significant after controlling for quality of learning. Another mediating factor can be self-regulation, as some theories suggest motivation only leads to the decision to act.
Finding of Studies Performed on Motivation and Achievement
Most studies (this article summarized multiple studies) investigating the reciprocal relationship between motivation and achievement have measured motivation through questionnaires probing academic self-concept (e.g., the Academic SelfDescription Questionnaire by Marsh & O’Neill, 1984). The studies interpreting the connection between motivation and achievement lack a causal relationship. In almost every study investigating reciprocal motivation and achievement relations, the need for experimental designs, in which either motivation or achievement is manipulated, is raised as a suggestion for future research.
The Influence of Motivation on Achievement
All the theories examined suggested that there are positive influences of motivation on achievement and vice versa. There is also a very strong relationship between motivation and student achievement. One of the hardest problems to solve is the lack of studies that allow for firm causal inferences. While there are studies that lack a controlled variable, there are other studies that do have a causal effect but consist of a third or hidden variable.
Notable Quotes:
“This led to a research agenda consisting of the following recommendations for future studies on the relationship between motivation and performance: (1) include multiple motivation constructs (on top of ASC), (2) investigate behavioral mediators, (3) consider a network approach, (4) align frequency of measurement to expected change rate in intended constructs and include multiple time scales to better understand influences across time-scales, (5) check whether designs meet the criteria for measuring causal, reciprocal inferences, (6) choose an appropriate statistical model, (7) apply alternatives to self-reports, (8) consider various ways of measuring achievement, and (9) strive for generalization of the findings to various age, ethnic, and sociocultural groups.”
“We argued that the strongest support for causal claims on motivation-achievement relations would be studies manipulating either motivation or achievement at one time point and studying the effects on motivation-achievement interactions across subsequent time points.”
“…there might be culture-dependent or population-specific pathways connecting the relationship between motivation and achievement.”
Summarized Article:
Vu, T., Magis-Weinberg, L., Jansen, B. R. J., van Atteveldt, N., Janssen, T. W. P., Lee, N. C., van der Maas, H. L. J., Raijmakers, M. E. J., Sachisthal, M. S. M., & Meeter, M. (2022). Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda. Educational Psychology Review, 34(1), 39–71. https://doi.org/10.1007/s10648-021-09616-7.
Summarized By: Michael Ho
Identifying the interrelationships between self-regulation, emotion, grit and student performance by using the Cyclical Self-Regulated learning model, which is associated with a K-12 math tutoring program.
What happens when students fail in their academic tasks?
When students repeatedly fail at a task, their self-confidence in the subject goes down, and their anxiety and frustration goes up. They build a resentment towards the subject and start to believe that their time in class is not useful.
The concept and long-term nature of grit helps students maintain consistent and focused interest for important and challenging goals.
Improving the level of grit in students
Two groups of middle schoolers who were participating in a weekly Mathspring Intervention program were chosen, one based in the US, and the other in Argentina. The levels of grit and expectation of success were measured in these groups. The research team argues for the need to work on improving the level of grit in students, by validating hard work ethic, strengthening student setbacks, and encouraging diligence. It was also found that grit in the early phase of learning predicts success in later stages of learning.
More research needs to be done on student experience
This study is just the tip of the iceberg on representing types of student learning. More research needs to be done on the experiences of students with diverse learning patterns, and patterns found for students with disabilities, gifted students, easily-frustrated students and so on.
Notable Quotes:
“In education settings, students who exhibit self-regulation in learning behaviours are able to direct their efforts toward achieving academic goals.”
“There are certain traits and dimensions of character other than intelligence that are strong determinants of a person’s unique path towards success despite setbacks.”
“The long-term nature of grit is what differentiates it from similar constructs such as self-control and conscientiousness.”
Personal Takeaway
Reading this research has opened my mind to the importance of building grit in students, especially those in Learning Support, as this skill will strongly contribute to their future success in life and allow them to persevere through the challenges of life with more ease.
Shekufeh Monadjem
Summarized Article:
Kooken, J. W., Zaini, R., & Arroyo, I. (2021). Simulating the dynamics of self-regulation, emotion, grit, and student performance in cyber-learning environments. Metacognition and Learning, 16(2), 367-405.
A meta-analysis of factors which impact student motivation.
What factors have the greatest impact on motivation?
Students’ need for competence and teachers’ autonomy support for students has the greatest impact on student motivation. Other factors like quality feedback also impact student motivation, supporting Hattie‘s claim that teachers are at the forefront of student achievement.
The most influential factors on student motivation
The authors thoroughly identified studies which matched strict criteria and designed a coding spreadsheet to find correlation between factors, identifying how each factor impacted student motivation. This allowed them to identify 144 studies with over 79,000 students ranging from primary to university age. The study also examined the impact of teacher and parent autonomy support as aspects that impact motivation. The need for competence and autonomy support from teachers were found to be the most influential factors on student motivation. The authors also highlight other aspects within schools such as low pressure and quality feedback as correlating aspects influencing student motivation. The study also supports Hattie‘s claim that teachers are essential in student achievement.
Autonomy support vs reward and punishment
The study emphasized that teachers ought to be allowed to practice autonomy-support methods rather than use rewards or punishment. Yet these methods are also effective even when they are applied in a non-high-pressure environment where testing or result-driven pay is not prevalent.
Notable Quote:
“Results show that teacher autonomy support predicts students’ need satisfaction and self-determined motivation more strongly than parental autonomy support. Specifically, they show that regardless of age, school level, nationality, or gender, autonomy support predicts autonomous types of motivation, thereby providing support for existing interventions designed to increase student need satisfaction and motivation through autonomy-supportive practices. These results concur with Hattie’s (2009) meta-analysis of 800+ student achievement predictors showing that teachers are at the forefront of learning experiences for students and are likely to have the strongest influence on student motivation.”
Personal Takeaway:
It resonated with me because I believe teachers have a great influence on student motivation and achieving competence. Moreover, the correlation between teacher support and quality feedback is very interesting. I will aim to embed more autonomy support in my teaching and avoid rewards and punishment where possible because my setting would allow for such autonomy-support methods to be implemented. Furthermore, it aligns with the MARIO framework principle of developing student self-efficacy and self-directed learning using the MARIO approach in all that we do in the classroom.
Frankie Garbutt
Summarized Article:
Bureau, J. S., Howard, J. L., Chong, J. X., & Guay, F. (2021). Pathways to student motivation: A meta-analysis of antecedents of autonomous and controlled motivations. Review of Educational Research, 92(1), 46–72. https://doi.org/10.3102/00346543211042426
Key Takeaway:
More students with disabilities (SWD) are attending college today than ever before; yet, limitations of the current research base preclude the identification of evidence-based predictors of college success for SWD. However, several studies present promising evidence to influence post-secondary outcomes through the development of student-centered skills (i.e., learning and study strategies and self-advocacy). —Ashley Parnell
Establishing Evidence-Based Practices for Postsecondary Experience
More students with disabilities (SWD) are attending college today than ever before, with SWD accounting for more than 19% of all undergraduate students.1 While the presence of a disability does not negatively influence eventual graduation, SWD take longer to graduate and often find the transition to college more difficult than students without disabilities.2 As such, identifying evidence-based practices and predictors would help practitioners to better support secondary transition and the postsecondary experiences of SWD.
The purpose of this systematic literature review was to determine whether evidence-based practices can be identified that influence or predict college success for SWD. Researchers identified 28 studies that analyzed factors related to student GPA, retention, and graduation according to their inclusion criteria.
Articles were rated according to a modified version of the NTACT Quality Indicators criteria for correlational research to determine if sufficient information existed to identify evidence-based, research-based, and promising practices related to factors that impact student success. However, too few studies met these criteria indicating that the research base is not yet robust enough to confidently report evidence-based practices. Given the paucity and reasonable quality of the identified research base, the research team decided to move forward with the analysis of all articles.
Moving Forward: Practice Implications & Future Research
The results of this analysis provide researchers and practitioners with key takeaways specific to future research and secondary transition planning.
Results suggest several critical implications for secondary transition:
- Student-specific factors (i.e., characteristics & skills) rather than institutional factors influenced or predicted success in college.
- Self-advocacy and understanding one’s disability, including one’s strengths and needs (including academic accommodations), should be a critical part of secondary transition planning.
- Learning & study skill instruction should be infused throughout secondary academic coursework.
To grow & develop the current research base, the research team suggests:
- Increases in research funding to support identification of research-based practices for improving postsecondary outcomes for SWD.
- Employ more rigorous methodologies and examine long-term measures.
- Further examination of predictors such as self-determination, college readiness, social connectedness, and integration.
- Inclusion and consideration of student demographic details.
Summarized Article:
Madaus, J. W., Gelbar, N., Lyman, L. D., Taconet, A. & Faggella-Luby, M. (2020). Are there predictors of success for students with disabilities pursuing postsecondary education?. Career Development and Transition for Exceptional Individuals, 44(4), 191-202.
Summary by: Ashley M. Parnell — Ashley strives to apply the MARIO Framework to build evidence-based learning environments that support student engagement, empowerment, and passion and is working with a team of educators to grow and share this framework with other educators.
Additional References:
- National Center for Education Statistics. (2019). IPEDS 2019-20 data collection system. United States Department of Education.
- Knight, W., Wessel, R., & Markle, L. (2018). Persistence to graduation for students with disabilities: Implications for performance-based outcomes. Journal of College Students Retention: Research, Theory, & Practice. 19(4), 362-380.
Article Abstract
This article presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of self-efficacy. It is hypothesized that expectations of personal efficacy determine whether coping behavior will be initiated, how much effort will be expended, and how long it will be sustained in the face of obstacles and aversive experiences. Persistence in activities that are subjectively threatening but in fact relatively safe produces, through experiences of mastery, further enhancement of self-efficacy and corresponding reductions in defensive behavior. In the proposed model, expectations of personal efficacy are derived from four principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. The more dependable the experiential sources, the greater are the changes in perceived self efficacy. A number of factors are identified as influencing the cognitive processing of efficacy information arising from enactive, vicarious, exhortative, and emotive sources. The differential power of diverse therapeutic procedures is analyzed in terms of the postulated cognitive mechanism of operation. Findings are reported from microanalyses of enactive, vicarious, and emotive modes of treatment that support the hypothesized relationship between perceived self-efficacy and behavioral changes. Possible directions for further research are discussed.
MARIO Connections
This study has informed how intrinsic motivation and the development of self-efficacy are supported in the MARIO Framework. Bandura’s framework directly relates to the intentional design of personalized goal setting, feedback cycles, self-assessment and self-reflective practices as well as the choice of high-Impact learning strategies found throughout the MARIO Framework.
Article Abstract
Person-centered education is a counseling-originated, educational psychology model, overripe for meta-analysis, that posits that positive teacher-student relationships are associated with optimal, holistic learning. It includes classical, humanistic education and today’s constructivist learner-centered model. The author reviewed about 1,000 articles to synthesize 119 studies from 1948 to 2004 with 1,450 findings and 355,325 students. The meta-analysis design followed Mackay, Barkham, Rees, and Stiles’s guidelines, including comprehensive search mechanisms, accuracy and bias control, and primary study validity assessment. Variables coded included 9 independent and 18 dependent variables and 39 moderators. The results showed that correlations had wide variation. Mean correlations (r= .31) were above average compared with other educational innovations for cognitive and especially affective and behavioral outcomes. Methodological and sample features accounted for some of the variability.
MARIO Connections
The MARIO one-to-one relationship between educator and student is deeply rooted in Cornelius-White’s meta-analysis. This is particularly true for elements relating to the growth of independent student learning behaviors including, but not limited to, motivation and effort.
