Applying Learning Theories to Guide Instructional Practice

Applying Theory and Research 

            The following presents findings extracted from scholarly works that address learning theories' applications for resolving worldwide dilemmas related to human-welfare issues.  Human-welfare issues relate to societies, cultures, ethics, economies, governance, and communications.  The information from existing research answers the manner in which learning theories guide instructional strategies for post-secondary e-learning.  Also included are examples of learning theories applied within learning environments, and assessments of the appropriateness of those theories.       

Applying Learning Theories to Guide Instructional Practice

            Christensen (2008) wrote that every learning setting includes learning goals that require instructional strategies specifically focused toward achieving each goal.  Consequently, each goal requires one or more learning theories tied to learning strategies.  Organizing the dozens of learning theories into succinct categories aids an instructor's decision-making required for each learning setting.  Christensen (2008) explained that four categories aid instructors in designing teaching activities as each learning setting arises.  The "behavioral, information processing, psychological/individual constructivist, and social/situated constructivist views" (Christensen, 2008, p. 27) represent such categories. 

            An example of an instructor's learning theory selection process for guiding students in solving a problem related to a current societal issue may combine the social constructivist and behaviorist learning theories (Christensen, 2008).  Combining these theories presents learning activities wherein students co-construct knowledge via learning teams, and the instructor uses motivational strategies from the behaviorist theory in connection to the learning activities by providing extra points for exceptional teamwork (Christensen, 2008).     

            Christensen (2008) provided insight regarding designing instruction based upon one or more instructional issues such as training, preparation, and education.  The appropriate learning theories for training learners who need improvement or an upgrade in computer skills could use Bloom's mastery learning model, Skinner's program instruction, or Keller's personalized systems of instruction (Christensen, 2008).  Combining theories to transition learners from training to preparation provides instructors with an opportunity to teach learners "critical prerequisite concepts necessary for performing a job" (Christensen, 2008, p. 30).  Applying learning theories such as "Ausubel's meaningful reception learning or Gagné's theory of instruction" (Christensen, 2008, p. 30) supports this transition. 

            Finally, if the instructional problem requires further learning, such as working cooperatively in teams while solving work problems, learning theories added to the previous two stages could include "Schank's goal-based scenarios, Savery and Duffy's problem-based learning, or Michaelsen's team-based learning" (Christensen, 2008, p. 30).  The instructor includes considerations of "time, cost, and contextual constraints" (Christensen, 2008, p. 30).  By selecting theories that can achieve maximum learning, achievement of instructional goals  increases exponentially.

            A study by Hamat and Embi (2010) indicates that the constructivist learning theory represents the philosophy applicable to a set of several learning theories.  From a learner's perspective, the set involves constructing knowledge.  From an instructor's perspective, the set requires supporting learners as knowledge is constructed.  The four principles embodying constructivism explain that learners' interfaces with the environment and experiences provide deconstruction and reconstruction of the learning matter using "assimilation and accommodation" (Hamat & Embi, 2010, p. 238).  As learners accommodate the reconstruction process, a "higher level theory or logic" (Hamat & Embi, 2010, p. 238) occurs.  Constructivism's third principle explains that student learning derives via "investigation, predicting, imagining, manipulation of information and invention" (Hamat & Embi, 2010, p. 238).  Reflection occurring during the development of learner's constructs focuses upon resolving conflicts (Hamat & Embi, 2010).  

Important Issues Attributable to Applying Learning Theories to Practice

            Nworie and Haughton (2008) remarked that online instruction has posed new issues for teachers due to disruptions from learning caused by "instant messaging, computer games, web surfing, and personal projects" (p. 52), which adversely impacts an effective application of learning theories.  Furthermore, instructors, and students develop technological skills at varying levels.  Even as instructor's intentions for improving learning via new and quickly changing technologies persist, such changes impede rather than construct learning.

            The Law of Unintended Consequences explains that unexpected effects that accompany change cause unanticipated negative or positive results (Nworie & Haughton, 2008).  The introduction of new e-learning tools cause such effects.  Unanticipated results caused by "ignorance, error, immediacy, basic values, and self-defeating prophecy" (Nworie & Haughton, 2008, p. 54) arise from instructors who fail to fully examine and comprehend the implications of using new technologies. 

            Consequently, sustained by standard operating procedures, instructors roll out previously used teaching strategies without allowing for disruptions to learning theories.  Not reflecting upon possible unintended consequences marginalizes learning.  As instructors increasingly convert teaching strategies to the online class, budgeting restrictions and development creates new issues that require revisions in the selection of appropriate learning theories (Nworie & Haughton, 2008).  Evolution conflicts with sensitive equilibriums inherent within instructional systems and processes.   

            Gijbels, Segers, and Struyf (2008) investigated if a constructivist learning episode shifted learners into deeper learning.  In addition, Gijbels et al. (2008) examined students' perceptions of increasing assessment demands.  Learners were differentiated by either a restricted or variable learning approach (Gijbels, Segers, & Struyf, 2008), which impacted transitions to higher or lower surface learning.  The study by Gijbels et al. (2008) disclosed that increased deep learning was not achieved in a "constructivist learning and assessment environment" (p. 435).

            Specifically, the restricted learning approach demonstrated a low variability in both deep and surface learning attributes.  Conversely, the variable group demonstrated high variability in deep and surface learning attributes.  Therefore, the depth of learning approaches was affected by learners' perceptibility, and limited an ability to change learning approaches.  The constructivist learning theory states that knowledge is actively constructed by the learner.  Apparently, instructors should consider the study by Gijbels, Segers, and Struyf (2008) before applying the constructivist learning theory because inconsistent deep learning arises during active knowledge construction.  However, there is one caveat for instructors to consider, which is that Gijbels et al. (2008) suggested that their study's results needed further examination to strengthen validity.

            Snyder (2010) taps into the impact that constructivism bears upon instructional-design theories, which guides the selection of instructional methods.  Instructors who present "authentic learning scenarios and problems" (Snyder, 2010, p. 50) to learners proffer new information.  The new information merges with learners' current understanding and experiences, and results in knowledge construction.  Presenting authentic learning is by no means easily mastered, and some instructors are more challenged than others. 

            Therefore, "meaningful and transferable learning" (Snyder, 2010, p. 50) occurs at varying degrees from little to nearly limitless amounts.  In addition to the challenges faced by instructors, students at various levels in the construction process act differently to new knowledge and fail to resolve "physical, mental, or social dissonance" (Snyder, 2010, p. 50).  Skilled instructors sense such breakdowns in knowledge creation, and can anticipate and provide supportive information to prevent such issues.  Because students require improved electronic proficiencies to create solutions to the growing number of complex problems, an instructor's responsibility for recognizing, researching, and devising methods that enrich learners' constructive processes continues to increase. 

Examples of the Constructivist Learning Theory Applied 

            Gijbels, Segers, and Struyf (2008) tested previous researchers' empirical work in a non-constructivist learning environment.  The previous work concentrated upon students' intended and actual approaches to learning as new assessment methods were integrated (Gijbels, Segers, & Struyf, 2008).  The study intention of Gijbels et al. (2008) focused upon determining if a constructivist learning environment for education students altered learning approaches when provided with assessment requirements.  Apparently, a commonly accepted concept by instructors explained that students employ "surface and deep approaches" (Gijbels et al., 2008, p. 432) according to assessment demands.

            A description of the methodology used by Gijbels, Segers, and Struyf (2008) included an instructional goals-linked constructivist learning environment that blended active learning with assessments that provided the students with "guided self-study, activating lectures, two authentic group assignments, and two individual assignments" (p. 435).  Because the essay's focus is presenting application of the constructivist learning theory, the study findings by Gijbels et al. (2008) note only that learners do not change learning approaches toward deeper learning.  In addition, the article represented examples of the manner in which the constructivist learning theory was applied during an empirical research project.

            Gijbels, Segers, and Struyf (2008) recommended that instructors reflect upon learners' variability in learning approaches before using the constructivist theory.  For example, Gijbels et al. (2008) suggested that learners may require extra time to become accommodated to learning approaches, which provides a buffer so that instructors can aid learners in adapting.  In response to the need for a buffer, Lucariello (2012) suggested initiatives to instructors rolling out new learning concepts and theories.  For example, instructors' initiatives should provide learning opportunities that students perceive as "plausible, high-quality, intelligible, and generative" (Lucariello, 2012, para. 3).  Group discussions require learners' access to personal knowledge during the preparation of verbal responses (Lucariello, 2012).  Other initiatives included "model-based reasoning, diverse instruction, raising student metacognition, and epistemological thinking" (Lucariello, 2012, para. 3).

            Koohang, Riley, Smith, and Schreurs (2009) presented three components of constructivism in an e-learning model, which warrants a review due to the article focusing upon teaching business students online, which is part of the aforementioned specialization.  Koohang et al. (2009) presented several examples of their model in practice, and summarized 18 characteristics of the constructivist theory.  The model's three constructivist components included the "design of learning activities, learning assessments, and instructor's roles" (Koohang, Riley, Smith, & Schreurs, 2009, p. 94). 

            Designing learning activities referred to elements that embodied fundamental and collaborative designs espousing learning activities such as "collaboration, cooperation, multiple perspectives, real world examples, scaffolding, self-reflection, multiple representations of ideas, and social negotiation" (Koohan, Riley, Smith, & Schreurs, 2009, p. 94).  Instructors explained to learners that using "experiences and/or knowledge" (Koohang et al., 2009, p. 95) encouraged "interrelatedness and interdisciplinary learning" (Koohang et al., 2009, p. 95).  Consequently, the learning situation challenged learners to assimilate new knowledge that additionally pushed learners beyond their comfort levels (Koohang et al., 2009).

            The second component referred to elements explained as the learning assessment, which advocated assessments for the "instructor, learner collaboration, and self" (Koohang, Riley, Smith, & Schreurs, 2009, p. 94).  The third component portrayed as instructor's roles included  "coaching, guiding, mentoring, acknowledging, providing feedback, and assessing student learning" (Koohang et al., 2009, p. 94).  The students participating in the study by Koohang, Riley, Smith, and Schreurs (2009) were not informed of the model's use although feedback to students encompassed all components of their model.  Withholding the model's information could imply that Koohang's et al. (2009) team wanted responses driven by the learners rather than the learners attempting to second guess what the instructor might be seeking. 

            One of the assignments designed by Koohang, Riley, Smith, and Schreurs (2009) included an assignment for the e-learning business students.  Specifically, the assignment stipulated that learners investigate an actual knowledge management (KM) business.  Learners were required to investigate the online company's management and "improve its key performance indicators such as page views, server load, network traffic, and transactions per second" (Koohang Riley, Smith, & Schreurs, 2009, p. 96).  The instructor communicated the reading and writing assignment to the students, which required "clear, concise, and persuasive" (Koohang et al., 2009, p. 103) responses.

            Santally et al. (2012) questioned if e-learning could evolve with constructivism (a.k.a. socio-constructivism) as a new paradigmatic learning framework, and discussed possible implications for teaching and learning applications.  Santally et al. (2012) proffered principles for designing a learning system grounded in the constructivist learning theory that included:

            Learning (that) should be internally controlled and mediated by the learner…(focusing)    on realistic approaches to (solve) real-world problems…fostering reflective practice… …presenting authentic tasks…(enabling) context-and content dependent knowledge construction…(and) supporting collaborative construction of knowledge through social negotiation.  (p. 13)

            Santally's et al. (2012) project confirmed the application of the principles noted above.  For example, participants' remarks revealed (a) controlled learning; (b) that the design and teaching approaches sustained learners' focus by embracing "realistic and…creative approaches" (Santally et al., 2012, p. 13); (c) that learning journals demonstrated levels of efficiency and effectiveness that cultivated deep, reflective thinking; and (d) that authentic learning tools supported learning and application of new knowledge in various learning scenarios, such as in discussion forums and Facebook. 

            Peng, Su, Chou, and Tsai (2009) attempted to conceptualize a constructivist framework for  wireless mobile learning (m-learning).  Technologies have emerged as "intellectual partners, or mind tool(s)" (Peng, Su, Chou, & Tsai, 2009, p. 179) that augment constructive learning.  For example, learners increasingly choose e-tools and other electronic devices according to their potential learning value.  Also, potential learning values materialize as learners take advantage of accessing the Internet from any place at anytime with ever-increasing numbers of people and resources.  The most important impact upon knowledge construction that m-learning provides that differs from wired technologies includes "convenience, expediency, and immediacy" (Peng et al., 2009, p. 174).  Learners and instructors alike are increasingly challenged to learn as much and as quickly as possible how to maximize the utility of m-tools for knowledge construction.       

            Martens, Bastiaens, and Kirschner (2007) discussed the pressures from "constructivism, information, and communications technology on learning" (p. 81).  A study by Martens et al. (2007) using a constructivist e-learning environment (CEE) involved comparing the learning expectations of the study's developers to students' actual learning experiences.  The developers expected that if students were provided with a badly constructed assignment, students would be motivated to re-interpret the assignment, and in so doing, develop the skills required to find solutions (Martens, Bastiaens, & Kirschner, 2007).  Instead, students easily reconstructed the assignment, and unchallenged, found solutions using surface thinking.  Consequently, the developers wrongly anticipated students' reactions to the assignment although the students appreciated the challenge.    

            Martens, Bastiaens, and Kirschner (2007) concluded that although CEEs are used for generic students, instructors and researchers need to be more cognizant of the combined effects from learners' "characteristics, study outcomes, and appreciation of CEEs" (p. 90).  Developers and instructors must additionally acknowledge that an activity may seem to align with the constructivist theory when learners' perceptions of the activity does not align with the theory's activity.  Students' learning outcomes cannot be successful if a CCE does not assist learners in visualizing a bridge for constructing new knowledge. 

Appropriate Uses of the Constructivist Learning Theory 

            Gijbels, Segers, and Struyf (2008) suggested their study's results needed re-examination to strengthen validity because their study was the first of its kind.  Gijbels et al. (2008) found that executing constructivist learning, and an assessment environment did not result in students employing a deep learning approach.  By not presenting an activity that challenged learners, most students used surface learning techniques, which did not motivate learners to construct new knowledge for problem-solving.  Gijbels et al. (2008) additionally found that if students did not perceive that an activity and its assessment was difficult, knowledge construction was impaired.  Consequently, Gijbels et al. (2008) did not sufficiently apply the constructivist learning theory, which resulted in learners not constructing new knowledge. 

            The study by Martens, Bastiaens, and Kirschner (2007) somewhat mirrored the study by Gijbels, Segers, and Struyf (2008) because learners' perceptions impacted their research project.  Martens et al. (2007) did not appropriately apply the constructivist learning theory as seen in their unsuccessful attempt to use the theory to activate construction of learner's knowledge.  Research projects frequently ask questions that require purposely testing hypotheses using learning theories.  As a means to conduct a test, unexpected coincidental results may occur.  However, in the case of the research project by Martens et al. (2007), the study's unexpected outcome was due to failure in addressing generally accepted concepts known about the constructivist learning theory.  Martens et al. (2007) did not design their activity fervently enough to motivate the students because the team relied upon their perceptions instead of the students' perceptions.

            The article by Koohang, Riley, Smith, and Schreurs (2009) discussed above noted that the intention of the writers was to use students' feedback for their study.  Appropriately, the writers filed paperwork to an IRB, and the IRB approved the project's application as written.  The application provided a process to assure the study's participants that their answers would be confidential.  Koohang et al. (2009) accomplished a sound literary review, which supported the constructivist theory's principles within their model.  However, Koohang et al. (2009) did not include literature that contradicted or challenged the authors' findings.  Researchers have an obligation to present unsupportive literature as much as supportive literature. 

            Koohang, Riley, Smith, and Schreurs (2009) noted that their model was designed and presented in an earlier work by Koohang.  The model was applied in each case study presented in Koohang et al. (2009).  A wise recommendation by Koohang et al. (2009) included that other researchers test their model to determine if the model could be improved.  However, Koohang et al. (2009) did not recommend an empirical study by other researchers, which would test the model's reliability and validity.  Because Koohang et al. (2009) mentioned that the design of the model occurred before his team performed the case studies, this writer takes an objection to Koohang et al. (2009) retrofitting the students' feedback to the model's conceptual theories, which included the constructivist learning theory. 

            By retrofitting participants' feedback to a research model, some researchers could choose to modify feedback to fit their desired research outcomes.  In fact, others less familiar with the model may have accepted that the design represented an "advantage (when used) in e-leaning environments" (Koohang, Riley, Smith, & Schreurs, 2009, p. 92).  Koohang, Riley, Smith, and Schreurs (2009) fitted feedback to the model.  Subsequently, Koohang et al. (2009) declared that the model integrated all of the constructivism elements because feedback referred to each element.  Koohang et al.'s (2009) retrofitting probably biased the study, and invalidated the study's findings.

            Curious if Koohang had conducted an empirical study after the 2009 article, the author responded to an inquiry on November 1, 2012.  Indeed, Koohang published another article but did not conduct a scientific study of his model.  Instead, Koohang's purpose in his 2012 article was to advance concepts relative to the learning model presented in his previous 2009 article (Koohang, 2012).  Koohang (2012) indicated that the model was tested twice since 2009 and would be published in 2012.  Four years post the model's introduction, instructors employing the model by Koohang, Riley, Smith, and Schreurs (2009) may already know if the model helps or hurts learning. 

            Santally et al. (2012) based recommendations upon a wealth of literature but did not include a scientific test of their model.  Remarks by Santally et al. (2012) indicated their learning model provided "a new dimension to the conception of online distance learning courses" (p. 13).  However, the claim by Santally et al. (2012) is concerning because they sought to dispel criticism rather than conduct an empirical study that may have supported their integrated learning model.  If Santally et al. (2012) chose not to do an empirical study because they sensed such a study would not support their model, questionable ethical behavior could exist.

            The article by Santally et al. (2012) discussed two e-learning methodologies useful for achieving productive learning outcomes.  Santally et al. (2012) combined methodologies with e-tools such as an "e-book approach, rapid e-learning techniques, and online activity-based instructional design" (p. 13).  Santally et al. (2012) remarked that (a) constructivist supporters thought that the e-book learning approach merely dumps more information onto the electronic global information network rather than adding value to learning, and (b) rapid e-learning reduces interactions between the instructor and learner. 

            The differences between the first and second teaching method is that the first model presents learning resources such as "e-books, interactive quizzes, and exercises" (Santally et al., 2012, p. 10) for use in completing individual or group assignments.  The second model progressively adds resources relevant to the activities, and includes a more active instructor role. Both teaching methods employed constructivist principles that supported learner control, focused upon authentic problems needing reflection and resolution, provided "context and content dependent knowledge construction" (Santally et al., 2012, p. 10) while working with other learners.

            Santally et al. (2012) remarked that his approach created a new paradigm for e-learning that addresses criticisms of learning platforms, and provides a focus on the "educational transaction" (p. 13).  Unfortunately for the reader, Santally et al. (2012) did not scientifically test their proposed methods.   Because Santally et al. (2012) failed to test their proposed models, judgment of their models' value is untenable.  

            Peng, Su, Chou, and Tsai (2009) discussed a constructivist framework for wireless mobile learning (m-learning).  Technologies, in general, have emerged as "intellectual partners, or mindtool(s)" (Peng, Su, Chou, & Tsai, 2009, p. 179) that augment constructive learning.  For example, learners and instructors increasingly choose e-tools and other electronic devices according to their potential learning value (Peng et al., 2009).  Significant learning materializes as learners take advantage of accessing the Internet from any place at anytime with ever-increasing numbers of people (Peng et al., 2009). 

            Apparently, the most important effect from m-learning that differs from wired technologies relative to constructing knowledge are "convenience, expediency, and immediacy" (Peng, Su, Chou, & Tsai, 2009, p. 174).  Learners and instructors alike are increasingly challenged to learn quickly and completely as well as adapt the processes required of knowledge construction that maximize the utility of m-tools.  Other emerging challenges include competing learning technologies that confuse students and instructors alike, depletion of the available time for learning, and depression of instructor-activated creativity as learning activities are designed (Peng et al., 2009). 

            Peng, Su, Chou, and Tsai (2009) suggested that researchers interested in investigating the efficacy of advancing technologies such as m-learning to enlighten constructivist learning environments use their article's information.  There are countless numbers of such articles that summarize others' works, and propose new concepts.  However, without including a scientific study to test the reliability and validity of conceptual recommendations, using such a recommendation is difficult.

Conclusion 

            Exploring the application of learning theories in scholarly works leads to new discoveries for resolving worldwide dilemmas related to human-welfare issues.  These issues include problems related to societies, cultures, ethics, economies, governments, and communications.  The information from existing research answered the manner in which learning theories guided instructional strategies for post-secondary e-learning.  Also included were examples of learning theories applied within learning environments, and assessments of the appropriateness of those theories.      

References:

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Christensen, T.K. (2008, April). The role of theory in instructional design: Some views of an ID practitioner. Performance Improvement, (47), 425-32. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/pfi.199/pdf

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Hamat, A.,& Embi, M.A. (2010, October). Constructivism in the design of online learning tools. European Journal of Educational Studies, (2)3, 237-246. Retrieved from http://ozelacademy.com/EJES_v2n3_7.pdf

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Santally, M.I., Rajabalee, Y., Cooshna-Naik, D., Rodriguez, C.O., Dedić, V., Marković, S., ... &     Puxley, M. (2012, July 30). Learning design implementation for distance e-learning: blending rapid e-learning techniques with activity-based pedagogies to design and implement a socio-constructivist environment. European Journal of Open, Distance, and e-Learning. Retrieved from http://www.eurodl.org/materials/contrib/2012/Santally_et_al.pdf  

Snyder, M.M. (2009, January/February). Instructional-design theory to guide the creation of online learning communities for adults. TechTrends, 53(1), 48-56. Retrieved http://search.proquest.com.proxy1.ncu.edu/docview/223119414?accountid=28180