Renee Watson


Instructional design requires the selection of strategies to meet the needs of diverse learners in a way that is effective, accessible and motivating for all. Assuming John Keller’s ARCS Model of Motivational Design (Keller, 2010) is correct, and confidence is a key component to motivation, which has been asserted as essential for learning to take place, how does disability impact motivation? We must consider the impact on the aspects of confidence and success, even so much as to the relevance of what and how we are teaching to the learner once their attention has been captured.  Reducing barriers to involvement is only the beginning, much can be learned about how to increase engagement for all learners.

Literature Review

Emotional regulation has been linked to increased social interaction in online learning environments (Arguedas et al., 2016, para. 3) indicating its significance to productive involvement in the learning process. Emotions can provide teachers with the feedback necessary to make decisions about when and how to modify instruction to better meet the needs of the learners. Theoretically speaking, Bandura’s social learning framework (1982) considers self-efficacy critical to successful learning and foundational to self-efficacy is the concept of self-management (Arguedas et al., 2016, para. 6). Since time-management can also be viewed as “self-management since we manage ourselves to make the most of time,” (Arguedas et al., 2016, para. 6) time management must be evenly considered alongside motivation as a predictor of academic achievement. Consequently, there is a need to design a more responsive environment to compensate for skill deficits found in students with disabilities, as supported by Ford’s Motivational Systems Theory (MST) (Ford, 1995, para. 15). The basis for Ford’s theory is in the different roles played by the motivational and skill components of the learner. Ford surmises, “Motivational processes decide what to do; skill-related processes try to carry out those decisions (Ford, 1995, para. 16). The challenge for special educators then becomes how to motivate learners with disabilities to develop these essential skills. Ford contends, “skills are useless in the absence of motivation,” and the presence of motivation “can create conditions favorable to skill development” (Ford, 1995, para. 17).   Therefore, the presence of a goal that is “desirable, compelling and attainable” to the learner is required (Ford, 1995, para. 24). Such a goal must prioritize the learner’s “attention and activity” towards its pursuit. When instructional goals are out of alignment with the goals of the learner, intervention may be applied to facilitate realignment (Ford, 1995, para. 26). In the context of special education, this is more commonly referred to as accommodation.

The development of course material for students with learning disabilities has been analyzed with populations at risk of offending through the provision of court-mandated interventions through coursework. Components of programs enabling impulse control and problem-solving skills identified as useful to offenders must be introduced in specific ways to meet the needs of the diverse learners.  Flexibility on the part of the teacher has been linked to increased satisfaction, greater opportunity for individualized instruction, the development of personal goals, and in turn, increased relevance of course material to the learners (Goodman et al., 2011, para. 10). A theoretical basis can be found because lives that are fulfilling and beneficial may reduce the need for offenders to meet their goals through re-offending. Social skills training, including listening and talking skills, perspective-taking, and assertiveness skills can be taught in this way, increasing the problem-solving abilities of learners through the provision of structured opportunities for group work (Goodman et al., 2011, para. 13).

Research suggests academic self-concept (ASC) and academic achievement “are positively and reciprocally related to each other” (Pinxten et al., 2015). A strong correlation has been established between ASC and academic self-efficacy. The significance of this on special education is the least restrictive environment required for the delivery of instruction in order to meet the needs of all learners. Consideration should be given to the big-fish-little-pond model (BFLP Model), wherein students compare their academic performance with that of their immediate peers (Pinxten et al., 2015), as smaller resource settings may fail to provide the sea of learners necessary for optimal student growth as a result of such comparison.

Likewise, research indicates more instrumental questions are asked in an achievement structured environments compared to performance structured settings, which are often characterized by more expedient help-seeking. This suggests a relationship in how different classroom climate dimensions are linked to the types of help students seek as well as from whom (Schenke et al, 2015, para. 1).  Observed emotional support in the form of fairness, respect and caring was found to have a positive correlation with adaptive forms of help seeking and increased motivation, engagement and positive behavioral outcomes (Schenke et al, 2015).

Statistical analyses conducted on factors identified as predictors of learning disabilities (LD) such as motivation, metacognition, and psychopathology support there is an interrelationship of deficits in these factors. “Borkowski, Johnston, and Reid (1987) argued that children’s metacognitive knowledge impacts their motivation.  Peterson, Maier, and Seligman (1993) argued that children’s doubts about their academic abilities lead to ‘learned helplessness,’ which in turn leads to diminished expectations, efforts, and feelings of self-efficacy” (Sideridis et al., 2006).

Student and teacher characteristics, along with teacher instructional practices have been investigated using the Opportunity Propensity Framework in order to develop a deeper understanding of how students make gains in flexibility, also known as the ability to solve problems in more than one way (Star et al., 2015, para. 1). Under this framework, students must have the opportunity to learn, but they also must have the propensity to take advantage of the opportunity (Star et al., 2015, para. 2). Teacher questioning was found to be “critically important” (Star et al., 2015, para. 10) as well as the types of questions asked. Teacher and student data were collected from 8th and 9th grade Algebra 1 students across Massachusetts as part of a larger study. Students were given an 11-item measure at the beginning and end of the academic year on which they were provided two ways to solve each problem. Students were then asked to select which way would be best to solve the problem. Results supported the authors’ hypothesis that background, opportunity, and propensity were indeed positively linked to higher achievement in mathematics (Star et al., 2015, para. 45) and flexibility. Questions surrounding teacher questioning were also answered by the data, indicating the students who made the most gains were provided more opportunities for discussion and were asked more open-ended questions when compared to their peers.

Variables related to motivation have also been explored in regular, special, and alternative settings. Students in regular and special education settings have been shown to have higher levels of parental support than those in alternative settings (Wiest et al., 2001, para. 2). Regular education students have been found to have increased levels of anxiety when compared with those in special or alternative settings. Studies focused on student placement in regular education, special education and alternative education settings reveal relationships between academic achievement and perceived competence.

Practical Recommendations

Investigation of the role of motivation, metacognition, and psychopathology could help researchers and practitioners in their screening and treatment of LD (Sideridis et al., 2006, para. 3).  The cognitive processes of attention, memory, and reasoning are impacted as learners regulate themselves. An instructor’s facilitation of these through meaningful feedback can help to increase participation in online discussions, (Arguedas et al., 2016, para. 3) leading to increased engagement. Implicitly, recognizing the need for teachers to be skilled facilitators of learning strategies, we can design supports for these purposes, thereby increasing the time that can be spent on learning processes. The use of technology that supports emotional conveyance could assist teachers in identifying the needs of students as they change. Applications that allow for the use of emojis or programs that allow for the creation of personal avatars can both increase engagement and the likelihood feedback will be effective, increasing the potential for learner engagement.Constructivism, a teaching model of connecting new material to the learner’s past experiences (Akpan & Beard, 2016) in order to accomplish meaningful objectives can be especially effective in Special Education, though much professional development is needed for educators to understand how to transition to this way of teaching. Research in this area would be advantageous in raising awareness to the advantages of such strategies, as well as in determining the most effective ways to embed such instruction.

Careful attention to goal alignment in instructional design can produce win-win situations wherein multiple goals can be attained seamlessly.  An example could be the embedding of activities in games or simulations aligned with the learner’s interests or allowing for increased autonomy in the learning process. Also referred to as “goal insurance,” the methodical integration of multiple goals in a single activity is, Ford asserts, “one of the most productive habits an interventionist can develop” (Ford, 1995). As students become older, they increasingly consider the cost of asking for help whereas younger students are aware of this and determine whether to ask based on their perception of success. As students become more metacognitive, however, they employ more help-seeking strategies. This is important because help-seeking allows learners to learn relevant information that further supports future learning.


The findings and recommendations for practical application of motivational theory have been represented to show how learners with diverse needs can participate fully and equally in the learning, provided consideration is given during instructional design. Practical implications suggest emotional and behavioral deficiencies are important factors in the identifying of students with learning disabilities. More research is needed to determine if these are a result of “specific, developmentally limited cognitive deficits (i.e., negative Matthew effects) or, instead, comorbid characteristics (Sideridis et al., 2006). The historic emphasis on “behavioral, operant techniques to control the behavior of learning disabled and emotionally handicapped students (Wiest et al., 2001, para. 8) and its negative impact on students’ development of intrinsic motivation “since traditional operant techniques do little to help one initiate and regulate behavior internally (Wiest et al., 2001, para. 3). Students able to benefit from the feedback of significant others was found to “foster the development of competence,” which in turn impacts academic success. Teacher autonomy support was found to have a positive correlation with the motivational levels of high-school-aged students. Higher levels of achievement have been found in students with an internal locus of control than in students with an external locus of control (Wiest et al., 2001, para. 3). Findings imply the O-P framework could be used to analyze academic achievement in general (Lewis & Farkas, 2017). It was determined early propensity variables such as achievement and motivation can be predictive of placement, which in turn can be used to predict future motivation. There was little data on the impact of emotional awareness on time and self-management, which can also apply to all learners to increase engagement, thereby impacting achievement. Further research is necessary to determine ways instruction may be designed to reinforce emotional awareness, in turn increasing the cognitive engagement and self-regulation essential to the learning process.


Akpan, J. & Beard, L. (2016). Using constructivist teaching strategies to enhance academic outcomes of students with special needs. Universal Journal of Educational Research 4(2): 392-398 doi: 10.13189/ujer.2016.040211

Arguedas, M. Daradoumis, T., & Xhafa, F. (2016). Analyzing the effects of emotion management on time and self-management in computer-based learning. Computers in Human Behavior, 63, 517-529 doi:10.1016/j.chb.2016.05.068

Goodman, W., Leggett, J., Bladon, E., Swift, C., Treasure, T., & Richardson, M. (2011). The good thinking! course – developing a group-based treatment for people with learning disabilities who are at risk of offending. Journal of Learning Disabilities and Offending Behaviour, 2(3), 114-121. doi:http://dx.doi.org.esearch.ut.edu/10.1108/20420921111186606

Keller, J. (2010). Motivational design for learning and performance. Springer Science Business Media, LLC

Lewis, R. & Farkas, G. (2017). Using an opportunity-propensity framework to estimate individual-, classroom-, and school-level predictors of middle school science achievement. Contemporary Educational Psychology 51(9), 185-197. http://dx.doi.org/10.1016/j.cedpsych.2017.08.003

Pinxten, M., Wouters, S., Preckel, F., Niepel, C., De Fraine, B., Verscheren, K. (2015). The formation of academic self-concept in elementary education: A unifying model for external and internal comparisons. Contemporary Educational Psychology (41), 124-132. https://doi.org/10.1016/J.CEDPSYCH.2014.12.003

Schenke, K., Lam, A. Connelly, A. & Karabenick, S. (2015). Adolescents’ help seeking in mathematical classrooms: Relations between achievement and perceived classroom environmental influences over one school year. Contemporary Educational Psychology (41), 133-146, https://doi.org/10.1016/J.CEDPSYCH.2015.01.003

Sideris, G.D., Morgan, P.L., Botsas, G., Padeliadu, S., & Fuchs, D. (2006). Predicting LD on the basis of motivation, metacognition, and psychopathology: An ROC analysis. Journal of Learning Disabilities, 39(3), 215-229. doi:10.1177/00222194060390030301

Star, J., Newton, K., Pollack, C., Kokka, K. Rittle-Johnson, B., Durkin, K. (2015). Student, teacher, and instructional characteristics related to students’ gains in flexibility. Contemporary Educational Psychology 41(4), 198-208. http://dx.doi.org/10.1016/j.cedpsych.2015.03.001

Weist, D., Wong, D., Cervantes, J., Craik, L., & Kreil, D. (2001). Intrinsic motivation among regular, special, and alternative education high school students. Adolescence 36(141), 111-26. Retrieved from https://link-gale-com.esearch.ut.edu/apps/doc/A76498122/EAIM?u=tamp73569&sid=EAIM&xid=7e0f2ec8


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