Learning Reflection

In self-reflection, over the last eight weeks, after a deeper dive into the different approaches, strategic styles, and environmental issues that influence an individual’s ability to acquire new knowledge. The basic of learning is a subjective interpretation of the presented experience. This intrinsic synthesizing of information is still considered ongoing research in search of a direct correlation to the brain’s role in information processing through neuroscience (Eric, n.d.). My understanding of learning before analyzing the psychology of learning deemed learning a singular process in which individuals process stimuli. This, however, is proven incorrect by the influence of the environment in which instruction is facilitated. 

The principles of higher education, corporate learning, and overall adult learning, andragogy rely on guided, self-directed learning to promote information processing compared with prior experience or storage files retrieved from long term memory LTE (Conlan, Grabowski & Smith, 2003). There are four main theoretical approaches to define the learning process. Behavioralism, cognitivism, constructivism, and the newer addition connectivism, describe how learners absorb knowledge through an internal/external scaffolding to demonstrates a baseline understanding (Conlan et al, 2003)(Kerr, 2007). Behaviorism and cognitivism rely on guided instruction to synthesize information through direct information processing to replicate skills obtained from the facilitation. Constructivism and connectivism give a high level of influence to the social environment, personal learning network, PLN, to cognitively process, and a personalized view of knowledge (Cercone, 2008). It is important to note that not one learning theory is the sole answer in planning instruction. Learners effectively sort information in working memory, STE, to organize experiences for recall in LTE using dual-coding methods (Gutierrez, 2016). No one theory is the one-stop-shop for understanding. 

Andragogy requires the intrinsic motivation to navigate learning strategies and styles in the most effective way (Huett, Moller, Young, Bray, & Huett, 2008 ). Most often, the facilitation of material is presented online through interactive eLearning. Technology, in a generalized summary applying to instruction, enhances a learner’s PLN through machine-based learning (Conlan et al, 2003). Misconceptions stemmed from technology defined as computer influenced, or automatic information analysis leaves out the importance of interaction. Through simple technological tools such as infographics, gamification, and multi-media, they result in positive influences from diverse cultural backgrounds to advance an expert level of understanding (Cercone, 2008). Learning styles help define intrinsic motivation through prior confidence in knowledge in LTE recalled, and preferred individually. However, the task of tailoring media, resources, and the social environment to a specific learning style is relevant to the amount of time the instructor has to implement ideas and eliminate strategies that induce cognitive overload.

In conclusion, learning is a complex mixture of neuroscience and psychology. In instructional environments, it is vital to provide a framework for the knowledge presented to ensure that emotional responses from stimulus promote motivation and self-directed learning. 


Cercone, K. (2008). Characteristics of adult learners with implications for online learning design. AACE Journal, 16(2), 137–159. Retrieved from http://www.editlib.org/index.cfm?fuseaction=Reader.ViewAbstract&paper_id=24286

Conlan, J., Grabowski, S., & Smith, K. (2003). Adult learning. In M Orey (Ed.), Emerging perspectives on learning, teaching and technology. Retrieved from http://textbookequity.org/Textbooks/Orey_Emergin_Perspectives_Learning.pdf

Eric P. Jensen: A Fresh Look at Brain-Based Education – Teachers.Net Gazette. (n.d.). Retrieved from http://www.teachers.net/gazette/OCT08/jensen/

Gutierrez, K. (2016, June 21). What are personal learning networks? SH!FT eLearning. Retrieved June 8, 2020, from https://www.shiftelearning.com/blog/personal-learning-networks

Huett, J., Moller, L., Young, J., Bray, M., & Huett, K. (2008). Supporting the distant student: The effect of ARCS-based strategies on confidence and performance. Quarterly Review of Distance Education, 9(2), 113–126.

Kerr, B. (2007, January 1). _isms as filter, not blinker. Retrieved May 20, 2020, from http://billkerr2.blogspot.com/2007/01/isms-as-filter-not-blinker.html