Dakota N. Theory Review

Theory Review

Your name	Commented On
Dakota N	Samantha McFadden

Theoretical Points

This theory review will highlight important considerations concerning methods of accommodation for different learning styles, technology integration approaches for differentiating instruction, developing an adaptive learning style curricula, challenges associated with different types of learners, and best practices that are linked to positive learning outcomes for individual learning styles. The literature identifies a variety of learning styles including, visual and spatial, logical, sequential, auditory, linguistic, and kinesthetic learning styles (Alfonseca, Carro, Martin, Ortigosa, and Paredes, 2006; Rogowski, Talla, and Calhoun, 2014; Saeed, Yun, Sinnappan, 2009). The wide variety of literature on learning styles lead to inconclusiveness between research conclusions due to differing methodologies, measurement variables, and interpretations of results. In addition to the way people learn, research has also delved into if demographic factors play a role in preferred learning styles.

 One point of interest seen in the literature is whether 21st-century students are ready for technology to supplement their learning. Saeed, Yun, and Sinnapan (2009) explored student readiness by using action research. These researchers attempted to examine the interaction of different web technologies with students’ learning styles. The study was conducted with 204 student participants in a web programming course pursuing Bachelors or Masters of IT degrees (Saeed, Yun, Sinnappan, 2009, p.101). The majority of students exhibited blended learning styles except those on the visual-verbal scale where verbal dimension was dominant (Saeed, Yun, Sinnappan, 2009, p.101). Podcast, vodcast, email, and blog were the preferred technologies for sequential, visual, sensing and intuitive learners respectively. Results from the study also report that teaching approach was not biased toward any particular learning style. Ergo, it accommodated all learner types to achieve well-balanced academic performance. The results additionally suggest that today’s students are ready to experience new technologies in their study routines (Saeed, Yun, Sinnappan, 2009, p.105).

Another imperative point is matching learning styles to instructional method, which is reported on in research by Rogowski, Talla, and Calhoun (2014). They attempted to create a study that utilized instructional methods for auditory, visual, and verbal learning styles to see their effect on verbal comprehension in this study. Specifically, they delved into how verbal comprehension may be influenced by auditory or visual stimuli. They respectively used digital audio and e-text to explore this relationship. Their research had two guiding questions, what is the extent to which learning style preferences relates to learning comprehension and to what extent can predictions be used to match instructional method to learning styles (Rogowski, Talla, and Calhoun, 2014, p.66).

Conclusions from Rogowski, Talla, and Calhoun (2014) report that differences in preferred learning style were not predictive of learning compression. For example, students with higher auditory preference do not have higher potential for listening comprehension compared to other learning styles like visual. It is assumed these factors come down to a complex interconnected network of individual ability rather than preferred learning style. There were also no statistically significant findings that supported their second guiding question, which infers that providing instruction that accommodates a preferred learning style is not indicative of better learning outcomes or retaining information when compared to using other instructional methods. This finding, which contradicts some of the other literature on learning styles in the literature pool, provides an excellent devil’s advocate for how effective instructional methods are on specific learning styles.

 From this research we see it is possible that individuals may not necessarily connect with a preferred learning style. An example of this would be that a visual learner could learn better from listening to a podcast rather than seeing a video. Of course, a combination of both would lend itself to a cycle where one supplements the other and expands on content and additional information. This allows each format to strengthen an area where the other is weaker.  

Another key topic in the literature was the connection between learning styles and grouping students in a collaborative learning environment. Researchers Alfonseca, et al. (2006) looked at how several learning styles matched together in collaborative groups can impact their performance. In their study, they integrated a web-based e-learning platform and administered an index of learning styles questionnaire to classify learning styles. Group learning has become not only started to emerge in distance education, but in the business world many companies are also competing and communicating across a global work environment. For this reason, many new technologies are becoming common place to allow individuals to collaborate on projects across a borderless world.

In their research, Alfonseca et al. (2006) identified five different learning styles. Many of these traits overlap with similar traits reported by Saeed, Yun, Sinnappan, (2009) including, active-reflective, sensing-intuitive, visual-verbal, sequential-global, and inductive-deductive (Alfonseca et al., 2006). When it comes to this wide range of learning styles collaborating, learners feel most empowered in groups that have communication, openly exchange ideas, and have examples of peer work (Alfonseca et al., 2006). Additionally, groups work together when there is a wide variety of tasks to accomplish. As suggested by Alfonseca et al. (2006), learning styles and group dynamics can have an impact on performance.

Finally, demographic such as age, socio-economic status, and so on may influence preference for learning style. Some workplace studies have begun to look at how intergenerational differences may influence how individual’s learn, as well as how training can be adapted to better suit their learning needs (Urick, 2017). Another perspective to consider in this context is how integrating training with technology vs. traditional trainer-led classroom models influence the interaction between learner, instruction, and encoding information into long-term memory. In the literature, Urich (2017) reports that younger generation sample (born between 1976 and 1987) were much more likely to adapt to computer-based training; these results are similar to reports from previous literature on the influence of technology on learning styles. Conversely, members of their older generation sample (born between 1934 and 1965) tended to think technology-integrated was not effective for them. Those in this older group also reported to be more comfortable gaining experience from on-the-job training and mentorship, rather than instructor-led training in a classroom (Urich, 2017).

Applications of Learning Styles

Accommodating learning styles inside the classroom requires institutions to take into account the variety of learning styles into lesson plan design in order to champion them and foster a culture that supports each individual learning styles.  Utilizing learning styles in practice has many pragmatic advantages from benefiting group learning, curriculum construction, and instruction, to helping learners better encode information. It is imperative for educators and administrators to understand the impact learning styles have on education. This can further help bridge the gap when delivering content, as well as lend itself to helping the educator develop strategies to deliver content across multiple platforms and Medias.

Another point is accessing how demographic information plays a role in the complexity of learning styles. It is not uncommon to have intergenerational groups in a classroom or training session, especially with many adults working at older ages, and adult learners returning to higher education (Gast, 2013). Being able to diversify one’s teaching style to reach multiple learning styles may serve to strengthen the salience of the lesson. Alternatively, organizations with enough funds and knowledge of learning styles can offer specialized training for different groups (Urich, 2017).  Humans learn in many different ways, and for teaching to have an impact it requires instructors to consider all learning styles and implement a variety of methods to successfully affect students.

Much of all learning today includes various forms of technology; this is made apparent by the use of computers, smart devices, podcasts, VR and AR, and many more technologies being used in the classroom. These devices have been used to improve student learning by engaging multiple learning styles into the learning process. They are also used in typing papers, assignment submissions, and communication with classmates and instructors. As suggested by Saeed, Yun, Sinnappan, (2009), the world of technology is increasingly becoming integrated into education at all levels. Technology can be a great asset to the learning environment, but one must also consider factors such as age, socio-economics status, experience, skills, and bias toward technological use in educational settings; in the literature, Urich (2017) highlights how an intergenerational demographic factor such as age can influence learner’s preference for content delivery.

That is why meaningful learning requires educators and administrators to be mindful of how technology can supplement learning, as well how it may hinder it. One way to implement this is through offering tutorials and instructions to help learners overcome these obstacles. Alternatively, more specialized instruction catered towards those learners needs may help in their education and in training. Any tool is only effective if the user knows how to use it. It is imperative to not make broad assumptions on the knowledge and skills that learners possess with forms of technology. It is important for educators to understand how to best accommodate a wide array of learning styles in the classroom.

Reflection

Highlights.

I think some of the most significant part of my assignment is just assessing the complexity of learning styles. Educators have a significant challenge before them in finding instructional methods that accommodate the wide array of visual and spatial, logical, sequential, auditory, linguistic, and kinesthetic learning styles. It is an arduous task for sure. Another highlight is the correlations between learning styles and technology preferences. Findings from Saeed, Yun, Sinnappan, (2009) revealed that technologies such as podcast, vodcast, email, and blog are the preferred technologies for sequential, visual, sensing and intuitive learners respectively. These results can be taken into consideration in the planning process beforehand. Results from the study also found that the majority of students in the 21^st century are ready for the integration of new technologies in learning. It is important to not be too overly reliant though, as not all learners will respond to technology and may prefer more traditional methods of instruction.

Process.

My biggest lesson from this process is something previously mentioned, but perfectly summarizes the whole idea of learning styles. Humans learn in many different ways, and for teaching to connect learners to the material requires instructors to consider the whole host of learning styles and implement a variety of methods to successfully reach learners. Learning styles are an important part of the learner to take into consideration. Educators may integrate this information with lesson plans in order to enrich the education process. This is a staple of any student-centered method because it can enhance education and increase student engagement when appropriately taken into consideration. This makes it an important consideration in any learning environment.

 Table

	The main theoretical ideas –Be specific		Summary of application
Idea 1	Technology and Learning styles	Integrating different visual, auditory, linguistic Technologies in the classroom to supplement Learning. (e.g., podcasts, blogs, videos, etc…).
Idea 2	Intergenerational Effects on learning styles	How does a Demographic factor like age influence learning styles? People across different generations prefer different styles of learning. Younger generations report being comfortable with computer-based learning and training while older adults report hands-on-experience and mentoring.
Idea 3	Matching instructional methods to learning styles	A students preferred learning style is not always going to be the best way for a student to learn. Specialized instruction tailored to a learning style May not be the end-all-be-all. It is important to have diverse instructional methodology and have general content and activities that broadly reach a variety of different learning styles for all learners.
Idea 4	Learning styles in group work	Learners feel most empowered in groups  that have communication, openly exchange ideas, and have examples of peer work. Groups function better work together when there is a wide variety of tasks to Accomplish. Group dynamics can have an impact on performance

References

Alfonseca, E., Carro, M. R., Martin, E., Ortigosa, A., Paredes, P. (2006). The impact of learning styles on student grouping for collaborative learning: A case study. User Modeling and User-Adapted Interaction, 3(4), 377-401.

Gast, A. (2013). Current trends in adult degree programs: How public universities respond to the needs of adult learners. New Directions for Adult & Continuing Education, 2013(140), 17-25.

Rogowski, A. B., Talla, P., and Calhoun, M. B. (2014). Matching learning style to instructional method: Effects on comprehension. Journal of Educational Psychology, 107(1), 64-78.

Saeed, N., Yun, Y., Sinnappan, S. (2009). Emerging web technologies in higher education: A

case of incorporating blogs, podcasts, and social bookmarks in web programming course based on students’ learning styles and technology preferences. Journal of Educational Technology & Society, 12(4), 98-109.

Urick, M. (2017). Adapting training to meet the preffered learning styles of different generations. International Journal of Training & Development, 21(7), 53 – 59.