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.
“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.”
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.
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
Improving our understanding of the mindsets of students with learning disabilities (LD) will permit the implementation of meaningful supports. However, a pilot study was inconclusive whether or not the growth mindset self-beliefs of students with LD were in fact false growth mindsets, wherein students were more focused on effort than more effective resources for support. — Matt Piercy
A False Growth Mindset
Goegan, Pelletier, and Daniels (2021) conducted a pilot study that explored the mindsets of grade 12 students with learning disabilities (LD). Dweck’s (1999) mindset theory1 was the guiding framework, and the authors’ interest was not limited to whether or not students adopted growth or fixed mindsets but questioned whether there would be a clear emergence of false growth mindsets in students. A false growth mindset is one that simplifies the need for support to merely putting in more effort.
The authors investigated the following three research questions:
- Do students with LD score similar to peers on measures of fixed and growth mindsets?
- Within the group, do students with LD identify more with growth or fixed mindsets?
- How do students’ self-beliefs about having LD correspond with mindset messaging?
The findings indicated that students with LD do in fact score similar to their peers on measures of fixed and growth mindsets. Yet, when compared within the group, students with LD reported significantly higher growth than fixed mindsets scores. It was inconclusive whether this growth mindset was more than simply tacitly tied to a notion of effort, or what is termed a false-growth mindset.
When students were asked to self-report on what it means to have a learning disability, two common words surfaced: “hard/harder” (31% response rate) and “work” (25% response rate). For example, “I just have to try harder.” The word “just” was linked in 9% of the responses, suggesting growth equates to effort.
An honest evaluation noted the study’s limitations. “First, participants were a homogenous group of students from one province in Western Canada.” Further, the sample size was 100 students.
Intriguing, however, was the authors’ suggestion that future research “could be conducted to examine the communication of mindsets messaging from teachers and other school personnel and how the information is adopted by students generally, and students who identify with having a LD in particular, to support the development of accurate growth mindsets.” The intention is to better understand the mindsets of students with LD, so appropriate and meaningful supports can be provided.
Though there are mixed findings relative to whether or not students with LD identify similar levels of growth and fixed mindsets when compared to their peers, the authors remain optimistic about how commonly students, without regard to disability status, are adopting growth mindsets. “Teachers should be providing messaging to all their students that they can indeed grow with effort and appropriate implementation of learning strategies and supports.”2
Goegan, L. D., Pelletier, G. N., & Daniels, L. M. (2021). I Just Have to Try Harder: Examining the Mindsets of Students with LD. Canadian Journal of School Psychology, 0829573521998954.
Summary by: Matt Piercy — Matt appreciates how at the heart of the MARIO framework is a passion to develop relationships and a desire to empower students to uncover their purpose while building upon strengths. Further, Matt is inspired by how the MARIO team supports educators and is quickly and nobly becoming a collaborative force in pursuit of educational equity.
- Dweck, C. S. (1999). Self-theories: Their role in motivation, personality and development. Psychology Press.
- Dweck, C. S. (2007). Boosting achievement with messages that motivate. Education Canada, 47(2), 6–10.
Although students with learning disabilities (LD) may experience difficulties throughout their academic career, they can develop strategies to overcome them—at times, without professional guidance. Yet, “active use of mentorship, coaching and support service units for students with LD will also contribute to ensuring greater success in higher education.” —Frankie Garbutt
Firat (Adiyaman University, Turkey) and Bildiren (Adnan Menderes University, Turkey) were intrigued by the increase in number of students with learning disabilities amongst university students overall. They wanted to know how these students may experience difficulties when compared to neuro-typical students because only a small percentage of students with LDs eventually graduate from university.
What Was Measured
The researchers collected a range of qualitative data on one student with learning disabilities (defined as ongoing problems with literacy and numeracy as well as verbal language use). They measured the strengths and weaknesses of the student throughout his academic life (from preschool to university) and how the student worked to build methods to overcome barriers to their academic progress.
The participant’s strengths over his education career included motor development, problem-solving, social skills, a desire to develop, and self-advocacy. His weaknesses throughout his educational career included subject content, social skills, executive functioning, and metacognitive skills.
Many of the difficulties he experienced in primary school continued through university, while one of his specific weaknesses in preschool, social skills, became a strength in his university years.
He was able to develop strategies to succeed on his own by studying lessons, improving memory methods, and learning to speed read. Interestingly, the student had not been identified with learning needs until he entered university and took a course on learning disabilities. Alongside his academic career, the participant learned to grow his self-esteem with activities outside the classroom like “chess or wrestling.”
Recommendations and Limitations
“Socio-emotional and academic difficulties experienced by students with LD may also continue throughout their university education. In this context, academic staff may receive additional training for increasing their awareness on the requirements of students with LD and for learning how they can support these students better.”
There are limitations to this research because “the study was carried out with a single student in the final year of his university education. Accordingly, the opinions of a greater number of students could be examined to yield more generalisable insights.”
Furthermore, the study data relied on interviews with the participant which may be tainted by him not accurately remembering the strengths and difficulties he experienced throughout his academic career. “The acquired data are limited by the self-awareness level of the student. Hence, this can be taken into consideration in future studies and the opinions of the student can be taken together with those of their peers, students, and family members.”
Fırat, T., & Bildiren, A. (2021). Strengths and weaknesses of a student with learning disabilities: from preschool to university. Journal of Further and Higher Education, 45(7), 958-972.
Summary by: Frankie Garbutt- Frankie believes that the MARIO Framework encourages students to become reflective, independent learners who progress at their own rate.
Metacognitive awareness (MA) is a significant predictor of academic achievement, enabling learners to take charge of their own learning by increasing their self-reliance, flexibility, and productivity. Teachers’ ability to create learning environments that support the development of MA is crucial to successful, life-long academic and social-emotional learning. —Ashley Parnell
Three Core Components of Metacognitive Awareness
Metacognitive Awareness (MA) means being aware of how you think and learn, and involves the ability to reflect on, monitor, and evaluate your learning and learning strategies. This study sought to examine teachers’ perceived support for learners’ metacognitive awareness in relation to three core components of MA:
- Knowledge of learning objects—to foster declarative (knowing what) & conditional (knowing why) metacognitive knowledge, teachers stimulate student understanding of what they know, what they need to know, and why they need to know and then support students in goal-setting.
- Regulation of learning strategies—to cultivate the planning, monitoring, and debugging of learning strategies, teachers guide students in identifying their own learning strategies, utilizing problem-solving strategies to monitor and modify those strategies as needed.
- Self-evaluation—to guide self-evaluation of knowledge and regulation, teachers use questioning strategies to support the learning in evaluating their learning progress and associated learning strategies.
Differences in Perceived Support by Discipline
Specifically, the researchers explored the differences in perceived support of MA across teacher groups, including subject teachers in both vocational education and training (VET) (those who teach skills needed in working life) and general education (GE) (those who teach all-round education), in addition to special education teachers.
Participants included 1,045 secondary vocational education and training (VET) subject teachers, GE subject teachers, and special teachers in Finland. Using the Inventory of Teacher’s Metacognition Support (ITEMS), teachers rated their practice of instructional strategies and scaffolds that effectively support the development of the three-component model of MA.
Results revealed the following differences or lack thereof:
- Special education teachers support learners’ MA more than VET and GE subject teachers across all components except self-evaluation of knowledge of learning—an area which was better supported by VET teachers than special education teachers.
- Perceived support varied between groups of subject areas in GE (i.e. math, physics, & chemistry vs. biology & geography) and components of MA.
- Women systematically supported learners’ MA more than men.
- Experienced teachers provided slightly more support for students’ MA than less experienced teachers, particularly teachers holding a Master’s degree.
These findings, considered alongside the critical role of teachers in effectively teaching and supporting the development of MA through instructional practices, confirm the importance of:
- developing MA support capabilities during pre-service and in-service teacher education;
- increasing collaboration between junior and senior teachers;
- recognition of the value and impact of metacognitive awareness and understanding across all levels of education.
Kallio, H., Kallio, M., Virta, K., Iiskala, T., & Hotulainen, R. (2020). Teachers’ Support for Learners’ Metacognitive Awareness. Scandinavian Journal of Educational Research. https://doi.org/10.1080/00313831.2020.1755358
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.
Key Takeaway: Currently, there are many sound, evidence-based reading comprehension interventions. However, not all students will demonstrate an adequate response to these interventions. Therefore, as special educators, we need to be aware of how and why students respond to reading comprehension interventions and how attention affects reading comprehension. —Michael Ho
In their study, Amanda Martinez-Lincoln, Marcia A. Barnes, and Nathan H. Clemens (2021) used moderation analysis to investigate for whom and under what conditions reading comprehension interventions are most effective. The authors investigated the following research question: Do language status and pre-intervention levels of anxiety, mind-wandering, and mindset influence the effects of a computer-delivered or teacher-delivered inferential reading comprehension intervention in struggling middle school readers?
The study aimed to:
1) Determine whether students’ mind-wandering, anxiety, and language status were associated with a differential response to an inferential reading comprehension intervention among struggling middle school readers
2) Examine whether these effects varied across instructional delivery systems: teacher-led instruction, computer-led instruction, and a control group (program based on what struggling middle school readers typically receive)
Here are the major takeaways from the article:
- Inference-making, the ability to infer information that is not explicitly stated in the text, is a vital component to reading comprehension. Difficulties in making inferences to connect parts of the text1 and to associate texts with background knowledge2 have been linked to poor reading comprehension.
- Attention is a core component of engagement and is crucial to academic achievement, including reading comprehension. Martinez-Lincoln et al. (2021) refer to the 2016 study of Rabiner et al.3 and emphasize that “poor attention can negatively influence students’ long-term academic outcomes in reading and math and can increase risk for not graduating from high school.”
- The purpose of this study was to test the effects of three factors of attention—Mind-Wandering, Anxiety, and Mindset—across three instructional delivery systems in reading: Teacher-led Instruction, Computer-led Instruction, and a Control Group.
- In the study, 67 students in Grade 6 to 8 from three middle schools in the southwest USA were included. A stratified randomized procedure was implemented and students were assigned to one of the three groups: Teacher-led Instruction, Computer-led Instruction, and a Control Group.
- Measures in reading assessment included Test of Word Reading Efficiency 2nd ed., Sight Word Efficiency, Connect-IT Inferential Reading Comprehension Assessment, Bridging Inference Task, and the Wechsler Individual Achievement Test 3rd ed., Reading Comprehension. Measures in attention included Mind-Wandering Questionnaire, Multidimensional Anxiety Scale for Children 2nd Edition, and Mindset Survey.
- Among students with similar high levels of mind-wandering, students in the computer-delivered intervention were able to make better inferences on the Bridge-IT Near task, a part of the Bridging Inference Task. Mind-wandering did not have an effect in the teacher-led intervention; this may be due to verbal praise and encouragement reducing the influence of mind-wandering in this group.
- Compared to similarly anxious peers in the control group, Martinez-Lincoln et al., (2021) found that “students in the computer-led intervention performed better on a comprehension test that required them to make several different types of inferences.” It is important to note that higher levels of anxiety were positively correlated with higher levels of reported mind-wandering.
- The effects of mindset on inferential reading comprehension intervention were found to be similar. This could be due to the small sample size or to the general mindset measures not being as sensitive as reading-specific mindset measures.
- Martinez-Lincoln et al. (2021) found that English Learners (ELs) “scored lower overall than non-ELs on all reading measures.” ELs scored higher in the control group compared to ELs in the computer-led instruction. More notably, in the teacher-led instruction, the ELs’ performance did not significantly differ from those of non-ELs. This may be due to more in-depth feedback and additional examples provided in the teacher-led instruction.
- This study had some limitations, such that the sample size was relatively small and that it was not realistic to include and control all of the factors that may influence students’ responses to reading instruction. In addition, participants read and answered the student engagement questionnaires silently. Although an interventionist was present, it is possible that a student may have misread or misunderstood the statements in the questionnaire. Finally, not all students were receiving reading instruction in the control group.
- The inclusion of student characteristics and instructional elements, such as group size and delivery by a computer or a teacher, in future research may be essential for developing effective reading comprehension instruction for struggling middle school readers, especially those who are ELs, have high levels of mind-wandering, or have high levels of anxiety.
Martinez-Lincoln, A., Barnes, M.A. & Clemens, N.H. Correction to: Differential Effectiveness of an Inferential Reading Comprehension Intervention for Struggling Middle School Readers in Relation to Mind-wandering, Anxiety, Mindset, and English Learner Status. Ann. of Dyslexia 71, 346 (2021). https://doi.org/10.1007/s11881-021-00215-3
Summary by: Michael Ho—Michael supports the MARIO Framework because it empowers learners to take full control of their personalized learning journey, ensuring an impactful and meaningful experience.
- Cain, K., & Oakhill, J. V. (1999). Inference making ability and its relation to comprehension failure in young children. Reading and Writing, 11, 489–503. https://doi.org/10.1023/A:1008084120205.
- Cain, K., Oakhill, J. V., Barnes, M. A., & Bryant, P. E. (2001). Comprehension skill, inference-making ability, and their relation to knowledge. Memory & Cognition, 29, 850–859. https://doi.org/10.3758/BF03196414.
- Rabiner, D. L., Godwin, J., & Dodge, K. A. (2016). Predicting academic achievement and attainment: the contribution of early academic skills, attention difficulties, and social competence. School Psychology Review, 45, 250–267. https://doi.org/10.17105/SPR45-2.250-267.
Erik de Corte describes a progression in which earlier behaviorism gave way increasingly to cognitive psychology with learning understood as information processing rather than as responding to stimuli. More active concepts of learning took hold (“constructivism”), and with “social constructivism” the terrain is not restricted to what takes place within individual minds but as the interaction between learners and their contextual situation. There has been a parallel move for research to shift from artificial exercises/situations to real-life learning in classrooms and hence to become much more relevant for education. The current understanding of learning, aimed at promoting 21st century or “adaptive” competence, is characterized as “CSSC learning”: “constructive” as learners actively construct their knowledge and skills; “self-regulated” with people actively using strategies to learn; “situated” and best understood in context rather than abstracted from environment; and “collaborative” not a solo activity.
De Corte’s work defines how learning is currently understood to be an active, self-regulated, social experience rooted in authentic context. MARIO, in all aspects, espouses this view of learning. It is fundamental to how MARIO defines the learner’s role.
Key Takeaway: Students with a deep approach to learning tend to have character traits associated with openness, conscientiousness, and a “steady temperament.” Educators can focus on fostering these traits in the classroom to increase students’ self-awareness and self-management skills, which students use to motivate themselves, set achievable personal and academic goals, and develop a growth mindset. —Shekufeh Monadjem
In the first study of its kind, the author Paulo Moreira, together with a group of researchers, investigated how different personality traits influenced students’ attitudes towards learning. The research was conducted with a study group of 686 adolescents with different approaches to learning.
Two major approaches to learning were identified—the deep approach and the surface approach.
The Deep Approach: “When a student adopts a deep approach to an academic task, this is to say that their underlying guiding intention is to maximize intellectual understanding and extract meaning from the task. There is also an intrinsic motivation to learn.” The qualities of openness, conscientiousness, and a “steady temperament” have also been linked to personalities that show a deep approach. Studies have shown a positive association between the deep approach and academic performance.1,2
The Surface Approach: Academic performance is typically lower in those students who display a surface approach to their learning.3.4 “When a student adopts a surface approach, the guiding motivation is extrinsic to the task. The resulting strategies for a given task under this approach, such as rote learning, are characterized by low investment and low effort.”
Furthemore, other traits were identified in the study group:
- Novelty seeking—seeking new experiences with intense emotional sensations
- Harm avoidance—a tendency to respond intensely to negative stimuli
- Reward dependance—a positive response and maintenance of behaviour in response to rewards
- Persistence—the tendency to continue with a behaviour despite the absence of a reward
Students identified as having a deep approach to learning showed low harm avoidance, low novelty seeking, and high persistence, as well as high cooperativeness and high self-directedness. Whereas, those that adopted a surface approach to their learning showed an opposite pattern of high harm avoidance and low self-directedness as well as neuroticism. These self-regulatory aspects of personality are important for helping students gain a more adaptive approach to learning.
Students showing high persistence in their personalities were also found to be “ambitious, enthusiastic, and tireless overachievers.”5
Because character is changeable, it can be developed and improved with the help of interventions to gain a more mature outlook. Adolescents with a mature character might be described as “responsible, resourceful, socially tolerant, empathic, principled, patient, and creative.”6 “Consequently, one practical implication of the study is that teachers and schools may be able to use character-development interventions with certain types of students, (i.e., those with a steady temperament profile) to encourage more adaptive approaches to learning and their associated positive academic outcomes.”
Mindfulness-based interventions are also an option that can be used to influence students to strengthen self-esteem and sense of mastery (i.e., self-directedness). Likewise, the results of the study also suggested that different types of interventions would be effective for students with different personality types. Educator awareness of character traits associated with deep learning allows for evidence-informed interventions focusing on fostering these traits to be harnessed in the classroom.
Moreira, P. A., Inman, R. A., Rosa, I., Cloninger, K., Duarte, A., & Robert Cloninger, C. (2021). The psychobiological model of personality and its association with student approaches to learning: Integrating temperament and character. Scandinavian Journal of Educational Research, 65(4), 693-709.
Summary by: Shekufeh Monadjem—Shekufeh believes that the MARIO Framework builds relationships that enables students to view the world in a positive light as well as enabling them to create plans that ultimately lead to their success.
- Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387. https://doi.org/10.1037/a0026838
- Watkins, D. (2001). Correlates of approaches to learning: A cross-cultural meta-analysis. In R. J. Sternberg, & L. F.
- Diseth, A. (2003). Personality and approaches to learning as predictors of academic achievement. European Journal of Personality, 17(2), 143–155. https://doi.org/10.1002/per.469
- Diseth, A. (2013). Personality as an indirect predictor of academic achievement via student course experience and approach to learning. Social Behavior and Personality, 41(8), 1297–1308. https://doi.org/10.2224/sbp.2013.41.8. 1297
- Cloninger, C. R., Zohar, A. H., Hirschmann, S., & Dahan, D. (2012). The psychological costs and benefits of being highly persistent: Personality profiles distinguish mood disorders from anxiety disorders. Journal of Affective Disorders, 136(3), 758–766.
- Cloninger, C. R. (2004). Feeling good: The science of well-being. Oxford University Press.
This individual differences study examined the separability of three often postulated executive functions-mental set shifting (“Shifting”), information updating and monitoring (“Updating”), and inhibition of prepotent responses (“Inhibition”)-and their roles in complex “frontal lobe” or “executive” tasks. One hundred thirty-seven college students performed a set of relatively simple experimental tasks that are considered to predominantly tap each target executive function, as well as a set of frequently used executive tasks: the Wisconsin Card Sorting Test (WCST), Tower of Hanoi (TOH), random number generation (RNG), operation span, and dual tasking. Confirmatory factor analysis indicated that the three target executive functions are moderately correlated with one another, but are clearly separable. Moreover, structural equation modeling suggested that the three functions contribute differentially to performance on complex executive tasks. Specifically, WCST performance was related most strongly to Shifting, TOH to Inhibition, RNG to Inhibition and Updating, and operation span to Updating. Dual task performance was not related to any of the three target functions. These results suggest that it is important to recognize both the unity and diversity of executive functions and that latent variable analysis is a useful approach to studying the organization and roles of executive functions.
This study enriched our understanding of executive functions and how they interact or operate independently depending upon the task a student engages in. This increased awareness is present in both the design of our course elementary EF skills module and throughout the MARIO Framework when self-directed learning is referenced.
This work, a second edition of which has very kindly been requested, was followed by La Construction du réel chez l’enfant and was to have been completed by a study of the genesis of imitation in the child. The latter piece of research, whose publication we have postponed because it is so closely connected with the analysis of play and representational symbolism, appeared in 1945, inserted in a third work, La formation du symbole chez l’enfant. Together these three works form one entity dedicated to the beginnings of intelligence, that is to say, to the various manifestations of sensorimotor intelligence and to the most elementary forms of expression. The theses developed in this volume, which concern in particular the formation of the sensorimotor schemata and the mechanism of mental assimilation, have given rise to much discussion which pleases us and prompts us to thank both our opponents and our sympathizers for their kind interest in our work. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Piaget’s introduction of the term “schema” and discussion of how children assimilate new information, from the earliest of stages primarily through the sensorimotor system, has influenced MARIO’s conception of the developmental continuum of learning. This continuum is embedded within the structure of both the elementary and secondary frameworks.
This study investigates interpersonal processes underlying dialog by comparing two approaches, interactive alignment and interpersonal synergy, and assesses how they predict collective performance in a joint task. While the interactive alignment approach highlights imitative patterns between interlocutors, the synergy approach points to structural organization at the level of the interaction—such as complementary patterns straddling speech turns and interlocutors. We develop a general, quantitative method to assess lexical, prosodic, and speech/pause patterns related to the two approaches and their impact on collective performance in a corpus of task-oriented conversations. The results show statistical presence of patterns relevant for both approaches. However, synergetic aspects of dialog provide the best statistical predictors of collective performance and adding aspects of the alignment approach does not improve the model. This suggests that structural organization at the level of the interaction plays a crucial role in task-oriented conversations, possibly constraining and integrating processes related to alignment.
Fusaroli and Tylén’s study informs the MARIO Approach through their description of the synergy approach to dialog. Through an understanding of the nuances of a synergistic approach, MARIO Educators are able to foster deep connections with their students, resulting in greater outcomes for both.