Concrete and formal operations in learning

Concrete and formal operations are part of Piaget’s genetic epistemology framework.  This study of how knowledge is developed is based on cognitive structures that correspond with stages of development. Piaget theory of cognitive development identifies four cognitive structures of sensorimotor, pre-operations, concrete operations, and formal operations. 

As discussed by Culatta (2021) the concrete operational stage is roughly 8 to 11 years, and formal operations start roughly between the ages of 12 to 15 and last into adulthood. McLeod (2010) discusses the concrete operational stage as the beginning of logical and rational thinking, with an ability to work problems in reverse.  These operations are applied to physical objects, it is not yet possible to hypothesize or process abstract concepts.  For example, a child could see an object and answer questions based on what they observe and know. The formal operational stage, as discussed by McLeod (2010) is the ability to think and reason in an abstract manner.  This thought process does not require physical objects.  For example, deductive reasoning can be applied to predict outcomes and then apply a systematic approach to test an idea.  Most literature indicates Piaget’s theory is associated with constructivism.  This makes sense in the concreate and formal operations stages since previous knowledge is necessary to rationalize and reason.

One way to promote concrete operations is by using worked examples.  For children that could mean giving them a mathematical formula with the solution and requiring them to work through the steps to show how to get to that solution.  In adult training an HTML course could use completed blocks of code allowing students to make adjustments to see how other tags affect how the page looks and works.  In comparison to formal operations the HTML lesson would be having students create a page from scratch.  For children this could mean posing a mathematical problem where the actual functions need to be determined before actually working the problem.


Culatta, R. (2021) Genetic epistemology (Jean Piaget). Instructional Design. Retrieved from:

McLeod, S. (2010) Formal operational stage. Simply Psychology.  Retrieved from:,for%20planning%20regarding%20the%20future.

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Thoughts on analyzing instructional design within the workplace

In analyzing my system of interest, how the instructional design (ID) process can influence the organization as a whole, highlights common misconceptions within corporate systems.  On the surface ID processes appear to take time, which organizations consider a poor return on investment.  The old school thinking of Time is Money does not consider modern solutions that can elevate business practices and create efficiencies within an organization. 

In analyzing my system of interest, a key challenge for IDs is not receiving the feedback needed to develop and improve upon output.  This is due to the positioning of an ID in the whole system.  Information is received by stakeholders within a business unit, who are not versed in ID processes.  Communication is broke, cluttered, or non-existent.  Important information contains bias, IDs are fed reactive outcomes instead of root problems.  This results in output that might address some surface level questions or might be completely ineffective. 

This problem in our current system contributes to perspectives on the overall value of personal development.  Companies are quick to cut the training budget first.  Even worse, skilled IDs are not commonly used to their true potential within a training department.  The truth is we can work smarter instead of harder, fostering businesses engagement within emerging markets and become industry leaders.  This level of innovation has never before considered the role of an ID as influential.  ID processes focus on truly understanding all facets of a situation, and then clearly communicating how to problem solve.  Resulting in clear, concise, and unbiased perspectives that prepare individuals to raise the bar and exceed organizational goals.

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Systems understanding

What is a system? What is systems thinking?

A system holds a collection of different parts along with their relationships.  All together it forms a larger system or system of system, with a unified meaning.  When parts of a system are removed it is not the same as it was as part of the system.  This is because systems can interact in some manner.  For example, the output of one system could be the input for another.  The mere collection of information can make systems and science appear to be the same, but they differ.  Science has a hypothesis and prescriptive process to deep dive into a piece of a larger whole.  Boardman & Sauser (2008) mention science not considering relationships, but I believe in some cases adding a qualitative analysis could potentially consider relationships.  Regardless, systems are more emergent and considers relationships as a valuable part of the process.

Systems are not linear, but more of a heterogeneous collection.  In class (also discussed in reading) we talked about systems being as macro perhaps referring to an organization as a whole, and as micro as a single class. In addressing problems or failures in a system it might only be in one business unit and not the system as a whole.  Since systems interact one failed system can affect other systems. Once the one failed system is addressed the problem can organically repair in related systems.  This highlights the need for a systems thinking approach to identify the root of any failures. Systems thinking is taking in multiple perspectives and looking at a problem from every vantage point. Perhaps one of my favorite perspectives is from Boardman & Sauser (2008) “Systems thinking does not suppress or supplant perspectives; it adopts them and finds sense in their multiplicity and diversity, their surprise.” (p2) At a micro level individuals affected by the problem should be part of a discovery process to generate the array of perspectives needed.

In taking my understanding of what a system is, and how systems thinking approaches problems I strive to build a proficiency in analyzing problems and identifying pain points.  More specifically, I would like to be able to analyze complex unstructured problems and learn how to make sense of them.  Challenges that arise in business are never presented in a tidy package. Relationships, internal and external elements, and related interactions exist and don’t purposely or maliciously go awry, but there can be an organic shift and gradual deterioration.  I would like to be better equipped to apply a systems thinking approach to these challenges.


Boardman, J. & Sauser, B. (2008) Systems Thinking: Coping with 21st Century Problems (Systems Innovation Book Series) CRC Press. Kindle Edition.

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Is social science really a science?

Science is the study of phenomena in the physical world.  Knowledge is drawn about the phenomenon by observation and systematic experimentation (Encyclopedia Britannica). Scientists strive to gather this information without bias.  Types of science can be grouped by earth science and social science.  Earth science encompasses many subcategories like biology, astronomy, natural, and medicine.  Social science encompasses subcategories like psychology, anthropology, and economics. 

There has been an ongoing debate whether social science is an actual form of science.  To answer this we must consider if social science is capable of a systematic approach to observing and analyzing phenomena in the physical world. The answer is yes, and it is proven true in methodologies used like research design, data collection and validation.

Research design includes development of study goals, the rationale behind the research, developing conceptual and theoretical frameworks, and planning the trustworthiness of the information or data gathered.  The processes within the design have systematic approaches.  For example, establishing the rationale for the study would include an exhaustive review of current literature to identify how formal theory is situated and to identify common research gaps. 

Both qualitative and quantitative data can be collected in social science research.  In addition to actual statistics, data could be composed of interviews, field notes, documentation, surveys and participant generated input (Ravitch & Mittenfelner, 2018).  Although the results can be unexpected the approach is systematically planned and implemented.  By supplementing statistical data with a context social science is able to better explain a phenomena.  Rosenberg (2018) discusses the ability for natural sciences to progress faster than social science.  If social science based findings solely on statistics it would progress faster as well.

Social sciences employ numerous methods of validity to confirm reliability of research data. Some examples are descriptive, interpretive, theoretical and evaluative (Ravitch & Mittenfelner, 2018).  Descriptive confirms factual accuracy by including notes collected in qualitative research, transcription, and detailed project plans. Interpretive matches behaviors and perspectives of research participants.  Theoretical explains the phenomena through the use of existing theories.  This not only serves as a basis for the research but adds another level of confirmation for the theory by being able to repeat the methodology.  Finally, evaluation describes the data without bias or judgement of the research team inserted into findings.


Encyclopedia Britannica. Retrieved from

Rosenberg, A. (2018) Philosophy of Social Science. Taylor and Francis. Kindle Edition.

Ravitch, S. M. & Mittenfelner, N. C. (2015). Qualitative Research: Bridging the Conceptual, Theoretical, and Methodological. SAGE Publications.

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Communicating with technology requires mindful integration

In The Role Of Technology In The Evolution Of Communication Rogers (2019) indicates the communication evolution started with the electric telegraph in 1831.  Although there were some forms of long-distance communication it was the start of electrical engineering that made this telegraph accessible.  Innovation continued with major milestones like the telephone in 1849, which continued to be our primary source of long-distance communication until more recent times. It took the adoption of internet technology, which was made available to the general public in the 1990s, to communicate in a new way.  Email became a welcomed substitution for writing and mailing a letter. After the turn of the millennium broadband became readily available for home use.  This allowed faster connection than dial-up, even able to out work complex corporate networks. Computers had been getting smaller, internet service was the missing piece for seamless remote communication. Of course we want smaller computers and faster connections, which led to advancements in Smartphone technology.  Anyone that has fought with a Blackberry would not be surprised to see how easily the iPhone took over the market in 2007.  In essence we can communicate long distances from anywhere we desire.  This ability has forever changed how we do business, how we learn, and in general how we interact with others.

In my corporate Instructional Design job all communication requires technology since we have remote teams spread out all over the world, and work with international customers.  Meetings are conducted through online web conferencing.  Dropping by someone’s desk to chat is instead a conversation exchanged through a messenger. Technology offers us the chance to communicate with the entire world without the time and expense of travel. Companies can assemble the right talent without worry of location.  Along with the opportunities technology brings, there are also challenges.  First, the actual technology is not consistent across every domestic location and every country.  Internet service is limited in some areas, which results in an individual losing connection during a meeting or even missing the meeting because the service is down.  We become dependent on communication tools, but these systems can periodically go down.  The other challenge is how we present ourselves when communicating with technology, verses in person.  For example, an in-person ribbing would result in laughs but that loses the charm online.  Explanations in email need to be more succinct than we might speak.  Thoughts, feelings, and intentions are not always portrayed the way we intend when we communicate with technology.  This can lead to hurt feelings, a lack of empathy and communication breakdown. A general awareness and better attempts to understand others can help with this challenge.

In education the use of technology has varied greatly between schools, programs, and levels.  In How Does Technology Impact Student Learning? Himmelsbach (2019) discusses how some teachers found technology more of a hinderance than helpful.  She went on to note several advantages which included access to information that is not available within the confines of a school.  This brings an opportunity to create curriculum with more diverse learning activities, and even pull in subject experts from another part of the world.  Students can interact, learn, and grow beyond the confines of a brick and mortar classroom. Technology accessibility has been highlighted more with the onset of COVID19.  Previously students in lower income communities could get by without technology, but now the educational gaps are becoming more defined. It takes thoughtful integration to use technology for learning.  We can’t just add technology to education and expect everyone to work the same as before.  Just like in business we need to change and adapt, that means attitude, accessibility, and pedagogy.  Instead of widening the gap technology could be the tool that closes it. 

Since the use of technology in education is relatively new in some settings, old theories or theories with a basis from a different industry have been adapted. We have entered a time of educational innovation, which was long past due.  It is time to innovate the theories that provide a basis for methodologies, outcomes and elevation of results. This idea is highlighted in an article by Bower (2019). Mediated learning technology theories have typically been adapted from theories intended for other uses or loosely associated.  Bower (2019) combined these technology-mediated learning theories into an individual concept. This idea is meant to offer a more stable way to analyze computer mediated learning.  In this article one premise that resonated was “In technology-mediated learning settings, the role of teachers is to help optimise student learning outcomes and experiences through the purposeful deployment of learning technologies” (p1039) In this premise he discusses how design should be for optimal learning.  Considerations should include how feedback is given.  The design should address more than direct feedback but also the information highlighted in data analytics.  This will create a more holistic approach and address individualized learning needs of the students. Technology has evolved, business has evolved, it is time for education to evolve. 


Bower, M. (2019) Technology-mediated learning theory. British Journal of Educational Technology, 50(3), 1035-1048

Himmelsbach, V. (2019, March 15) How Does Technology Impact Student Learning? Top Hat. Retrieved from

Rogers, S. (2019, October 15) The role of technology in the evolution of communication. Forbes. Retrieved at

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Philosophy of learning

Just taking in information does not equal knowledge development.  In addition to information we must take in experiences, thoughts, and feelings.  This adds a context to the information and allows us to evolve.  We develop new knowledge and grow old concepts.  Knowledge must develop for learning to happen.  This explanation of knowledge could make a case for behaviorism, cognitivism, and constructivism.  Behaviorism believes that the actual response to the learning stimuli shows that learning has happened.  It fails to account for any physical changes happening in the brain or how a higher level of thinking is developed.  Cognitivism focuses on the process taking place in the brain when information is taken in.  Ertmer & Newby (2013) suggest that learning happens when the acquired information is organized and stored in the working memory.  Constructivism takes the theoretical underpinnings of both behaviorism and cognitivism.  Ertmer & Newby (2013) notes that although constructivism is closely related to cognitivism it differs in believing more in an individual’s interpretation of the world, placing individual and environment as important.  Behaviorism and cognitivism believe the environment has a large role in influencing the individual.

My personal philosophy of learning is closer to a cognitivist view.  Ertmer & Newby (2013) describe this as a mental process “that entails internal coding and structuring by the learner.” (p51) Learning happens when outside stimuli is taken in, then applied, challenged, and disseminated into other contexts.  Ultimately the stimuli are constructed into new uses that can innovate and problem solve in unique ways; not for the sake of doing it but because it is an appropriate solution. 

Ertmer & Newby (2013) note that in constructivism “Prior knowledge is used to establish boundary constraints for identifying the similarities and differences of novel information.” (p52) I disagree, if the goal is to not only recall, but problem solving with new knowledge there should not be boundaries.  Innovative thinking comes from developing new ways to apply knowledge instead of staying in a box.  Having prior knowledge is valuable. The knowledge transfer process is most successful when new information is able to attach to existing knowledge.  This process is how we grow our thoughts, feelings, and views.   This makes a case for empiricism, in the context that we start with less knowledge and continuously build.  The thought of our mind starting as an empty slate does not account for physical brain development which happens prior to birth and all the way into adulthood.  Cognitivists align more with rationalism.  Knowledge transfer has successfully happened when we are able to recall existing information.  When knowledge transfer happens, then learning has occurred.

In looking for examples of cognitive learning theories I came across this example presented by Stanković et al. (2018). They quote the works of Piaget and Vigotski that influenced the cognitive learning theory of multimedia learning.  This theory activates the functions of sensory memory, working and long-term memory. 

The cognitive learning theory of multimedia encompasses the stages of:

  • Multimedia learning: words and images are presented.
  • Sensory stimulation: Audio and visual senses are stimulated as the multimedia is received.
  • Working memory: temporarily holds and processes the audio and visual cues from the multimedia.
  • Long term memory: permanent holding for future retrieval.

There is a need to slightly edit this model, since that the version Stanković et al. (2018) discussed is more passive.  My revised model would fall under active learning and include stages of:

  • Multimedia learning: review old content and work in new content using words, images, and animation.
  • Sensory stimulation: Audio and visual senses are the first to receive information.
  • Working memory: Information is processed through the hippocampus and temporarily held in the working memory, but this will dissipate in roughly 6 seconds.  Although this time can slightly vary by learner (for me it is roughly 3 seconds).
  • Practice: Interactive activity to experience new information to a deeper level and enforce previous learning.
  • Multi-sense stimulation: audio, visual and kinetic functions are stimulated.  Information will again travel through the hippocampus but now it is also coming from executive functions in addition to sensory.  This second journey to the working memory will promote recall of new information before purging.
  • Long-term memory: Some of the multimedia learning attached permanently, however the practice offers a second opportunity for attachment.

My revised model should promote a higher level of attachment to the working memory since it has two chances to attach during the learning process.  In the past this type of multimedia development was not easy to achieve.  More recently the tools Instructional Designers use have advanced, allowing the ability to include a large variety of interaction. Cognitivists and behaviorists alike believe practice promotes the learning changes, and constructivists place a high value in the actual experience. 


Ertmer, P. & Newby, T. (2013) Behaviorism, Cognitivism, Constructivism: Comparing critical features from an Instructional Design perspective. Performance Improvement Quarterly, 26(2) 43-71.

Stanković, Z., Maksimović, J. & Osmanović, J. (2018) Cognitive theories and paradigmatic research posts in the functions of multimedia teaching and learning. International Journal of Cognitive Research in Science, Engineering and Education 6(2) 107-114

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Article review: Educational Technology: Conceptual Frameworks and Historical Development

Eraut looks at conceptual frameworks for educational technology, coupled with historical developments.  This article appears to be more of a theoretical opinion with a historical review of educational technology. There was a plentiful collection of historical literature.  So much in fact that more than one article theme could have been supported.

Overall, the way the article was organized made it difficult to read. A history of educational technology was discussed along with theories that Eraut found significant at that time.  As a historical writing the theoretical underpinnings helped to understand the logic, however the way it was organized made it difficult to follow the progression over time. 

Distinct points appeared to get lost, or veer off, which made the article difficult to follow. One example is section three the discussion about the systems approach.  This is an opportunity to discuss how this widely used framework has been adapted to educational technology.  The contribution of von Bertalanffy was discussed which digressed from how systems thinking was adapted to an educational technology setting.  

Conclusions could have better surmised the point of the article.  Article goals to “rethink educational goals and the role of educational technology in facilitating their achievement” (p1883) were not laid out. Instead the ending stated educational technology history showed “limited theories, poor quality products, and naïve approaches to implementation.” (p1898) Educational technology processes and concepts were appropriate for the time in which they were used. For example, Dale’s Cone of Experience was discussed in regard to early audiovisual implementation.  Although not an appropriate method in modern times it did suggest a logical approach for the technology that was available in the 1960s.  In reality, this historical approach could be modernized and show merit. To further contradict this ending statement works by greats like Piaget and Gagne could have been included to emphasize the value of theoretical approaches throughout history. Finally, the article was supposed to discuss conceptual frameworks, so this should have also been mentioned in the conclusion. 

Eraut discusses the need for future educational technology modernization in other areas like information technology, cognitive science, and critical theory.  This may be a reasonable observation for the time this article was written.  Today cognitive science is more widely addressing topics like game-based learning, personalized learning and human computer interactions.


Eraut, M. (n.d.) Educational technology: Conceptual frameworks and historical development. Retrieved from UNT Internal link

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Choosing research methods

What looks to be challenging for you about locating and applying a new research method?

My initial challenge was to identify potential methods, define what they are and how they should be used.  Then I can determine what looks interesting to me and think about how it will fit into my interests. 

As I researched and pursued meaning in various methodologies I went a little off-track thinking about a direction I wanted to take for my dissertation.  So, my new challenge is focus!  Naturally, I wanted to dig deeper into my dissertation ideas to see how that could work. 

After several days, the realization sunk in that I had made no progress for this class.  I decided to put all other work aside and focus.  This is when I ran into my third challenge, the cat.  She sprawled herself over my laptop and fell asleep, but I pressed on still able to type with three fingers.  Unfortunately, she was so warm and snuggly I succumbed and was soon fast asleep as well.

Ok, let’s try this again! 🙂

Which ones did you identify in class and which seems most valuable/interesting? Why?

In class I found the Soft Systems Methodology the most relevant to my current work and future goals.  If I go with this approach it would certainly need to be integrated with another approach to fit what I want to accomplish. This leads me to consider approaches that fit well with SSM or even other approaches.

Other approaches that I am looking at:

  • Cognitive Mapping methodology: Using visual diagrams like concept maps and mind maps to diagram a mental model of the cognitive process during a learning activity.  I think this is more of a process or technique than an actual framework. This could potentially be helpful in my dissertation allowing me to visually align learning cognition with tasks, outcomes, or design elements.

  • Qualitative comparative analysis: This mixed method approach consists of a qualitative step where data is analyzed qualitatively for causation, and then goes through a quantitative systematic review. I have already determined my research will incorporate some level of both quantitative and qualitative.  This process of analyzing empirical and descriptive data will very likely be incorporated into my research.

  • Phenomenography: the study of how people perceive the world.  As it applies to my research, it would be interesting to understand how participants perceive the knowledge they want to acquire, as well as did or did not acquire while participating in the game-based learning exercise.  Since I want to measure working memory it would be interesting to understand the individual perception of how training influenced their experience and compare it to the learning cognition quantitative data collected.


Dixon, R. (2014) Cognitive mapping techniques: Implications for research in engineering and technology education. Sprint, 25(2)

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Soft Systems and Instructional Design for Technical Training

Soft systems methodology (SSM) could easily be used in education as a means to identify learning gaps and make recommendations to fill those gaps.  This is associated with the seven steps to SSM that Zhong (2007) discussed:

  1. Identify the problem or challenge that needs to be addressed.  Zhong (2007) discussed SSM applicable for semi-structured and unstructured problems.

    Applying this to education is to identify the problem that training needs to solve.  For example, a common tech problem is an overload of helpdesk tickets.  Training on a specific application can be added to onboarding or as mandatory to give users the tools needed to resolve their own basic questions.
  2. The identified problem should be described.  Zhong (2007) suggested images as more beneficial than language.  The thought is language could have different meanings depending on the context, where as an image tells a very distinct story and sets a more creative thought process for future steps.

    In education resources can be gathered like error messages, screen shots and emails to identify key pain points.  Then this information can be categorized by level of difficulty.  This organization will help produce training that gets progressively more difficult.  This is important since pain points will likely vary by the type of user.  This step could very likely involve a mindmap which would allow freethinking and interactive movements to get organized.
  3. All systems associated with the problem should be defined.  Zhong (2007) suggests relevant systems should be selected, and defined at the root level, to add insight to the problem.

    Theoretical systems can be associated as appropriate, however all technologies related to the systems need to be identified in order to incorporate them in the right context in the training.
  4. Develop a conceptual model for each associated system.  Zhong (2007) best describes this as “Each root definition consists of six aspects: customer, actor, transformation process, (Weltanschauung) world view, owner and environmental constraints.” (p5733)

    This could be associated with the actual use case development.  Systems are gone through, and level of detail needed for each audience is identified.
  5. The problem that was identified in step two should be compared to the conceptual models developed in step four.

    The initial training challenge is compared to the use case to determine if this will actually resolve key problems.  If it does not adequately train on these issues it is important to go back to step two and walk through the process again to identify where it is wrong.
  6. Identify the change that is expected to happen and if this change is even possible.

    In the educational example this step could happen earlier in the process, or after all problems and systems have been analyzed.  This is where actual learning objectives are created.  Learning objectives must be included in all training since they fill two key roles.  First, they are a self-check for the Instructional Designer to make sure all necessary content was included in the training.  Second, they are used after the training is taken by a user to measure if learning actually happened.  If training was not successful, then the module should again be put through this process.
  7. Finally determine actions that can be taken to resolve the problem.

    Since large technical training modules are best consumed in small bites, this step can be used to match the training back with the problem.  Then additional training can be identified to fill remaining gaps, which would walk us through the process again.

Zhong (2007) discussed how SSM is not the end all solution to a problem, instead it is cyclical, answering certain questions and then identifying new questions.  As in technical training constant improvements are required to accommodate technology innovation, changes in jobs, and to address new challenges that may arise.


Zhong, Y. (2007) Soft systems methodology based on decision making knowledge integration,” 2007 International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, pp. 5733-5736.

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Critical Theory

What is the critical theory?

A form of social criticism that evaluates society as it relates to individual life, community, and culture.  More importantly it evaluates the social structures in place and how they affect specific groups.  As this applies to education it could encompass a study on ethnic groups, the socioeconomic status of those groups and how this influences educational opportunities.  The societal structure of education might not cater to or even include needs of the group being studied.

In understanding the critical theory, we have to understand the concept of critique.  Which is a form of knowledge that can be derived from how we relate to the world. Thompson (2017) best defined critique as “a means to relate what is perceived in everyday life with a deeper, more rational knowledge of that world.” (p2) The knowledge derived from critique is in essence what we are doing in critical analysis.  This level of consciousness not only applies to the societal process that we are studying, but also to the related subjective factors.  In analyzing educational opportunities for a specific ethnic group critique could relate reasons why the current societal structure did not take the needs of this group into consideration.

Critical theory has the potential to offer perspective beyond initial beliefs.  This new perspective can lead to a change or transformation in the current societal norm, creating a new norm that is more inclusive to al groups. Thompson (2017) identified the point of critical theory less as a means to create new social structures but more as a way to, “unravel the contradictions that already exist.” (p3)


M.J. Thompson (ed.), The Palgrave Handbook of Critical Theory. Palgrave Macmillan

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Applying CMDA

How could I apply computer-mediated discourse analysis (CMDA) in my research interests?

In researching cognitive influences that gamification can have on learning, CMDA can be used to identify how participant comfort level influences performance.  In fact, this approach would be effective for researching serious games in education as well.  Research participants that otherwise fit the requirements could skew findings because of their comfort level interacting with game-like features.  

In learning, students have varying degrees of comfort with technology, which can make learning with technology a hinderance in some situations.  Game-like learning activities are designed to motivate and excite students to keep them engaged with the content.  If the student is not comfortable with the game-like features they will struggle and not benefit from the actual content.  Jong et al. (2016) implemented a virtual mentor into a serious game.  The purpose was to assist nonplayer participants with game interaction.  Interviews with select control group participants noted their lack of game play experience hindered their ability to learn.  The findings indicated that nonplayer participants that had the mentor to help them interact with the game, showed significant improvements in learning achievement.

To implement in research message boards could be added to the gamification module, with some threads addressing technical challenges.  This application of CMDA would apply both quantitative and qualitative methodologies.  Overall assessment of scores can be analyzed, message board interaction can be analyzed and then associated with scores generated in the learning assessments.  This will add the context of technology comfort level with score leveling.

The integration of CMDA with gamification research can be used in two ways.  First, it is a means to validate quantitative scores since additional meaning will be added to why these scores were achieved.  For example, did the participant struggle with the actual content or did they struggle with the gamification interaction.  Second, if it is found that lower scores correlate to discomfort with the game-like features, then interviews could be done to identify potential design improvements.  For example, offer more detailed directions, create example modules to practice interaction before entering the actual module, or simplify interactions.

Jong M.S.Y., Shang J., Tam V.W.L. (2016) Using Non-player Characters to Scaffold Non-gamer Students in Serious Gaming. In: Spector M., Lockee B., Childress M. (eds) Learning, Design, and Technology. Springer, Cham

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What is CMDA and How Can I Use it?

In current days, the internet is a necessity for communication, day-to-day activities, business, and learning, to name a few things.  Social media interaction has added to the abundant amount of content generated.  It is hard to analyze any phenomena associated with internet interaction, since it is descriptive text.  CMDA allows us identify patterns in online interaction and describe the phenomena in an empirical manner. 

What did you learn about CMDA?

The first thing is to define Computer Mediated Discourse Analysis (CMDA). It is a research approach that observes behaviors in online interaction.  For example, the examination of comment posts to YouTube (as we did in class).  In the realm of learning technology, we could study the interaction between students on a discussion board of an internet-based learning environment.

CMDA theoretical underpinnings come from linguistic discourse but can provide insight into phenomena not directly related to linguistics. The approach is not a specific method, but a compilation of methods.  The methods chosen are based on the desired research. Like other frameworks a research question is posed, appropriate tools are selected, and data are gathered.  Depending on the type of analysis other processes would be incorporated to ultimately interpret the findings.

What appears to be useful? What may be challenging? Why?

CMDA can be qualitative or quantitative. This could be both useful and a challenge.  Using just quantitative methodologies will not account for the ambiguous descriptions generated in CMDA.  Qualitative analysis should be incorporated to account for this data.  Likewise, including quantitative data with the descriptive qualitative nature of CMDA data can assist in grounding a diverse array of data.  At this point it appears that a combination of quantitative and qualitative approaches would result in a well-rounded empirical study.

A potential challenge is that a study focuses on the question, however unrelated influences could be inferred. The discourse behavior being analyzed offers empirical data however other behaviors not being studied could influence discourse.  These other behaviors are more inferred, instead of directly examined.  This comes down to making sure CMDA is the right approach for the study.  Phenomena that can be segregated from other factors are better suited for discourse analysis because of this limitation.

Are there specific settings in your own life as a researcher/practitioner where this may be the right method to answer your questions? Why or why not?

As an instructional designer CMDA can be beneficial in improving content and delivery of training.  Synchronous and asynchronous course interaction can be analyzed.  Student communication about the course, activities, and environment can be used to improve the learning experience.

In May I participated in the Artificial Intelligence course.  Among numerous forms of AI, we studied chatbots.  This led me to an idea to build a chatbot tutor and integrate it with gamification.  The chatbot would have access to the training a student engaged in, as well as related assessments.  Then the chatbot could offer encouragement, motivation, and guidance to continue development.  In the reference of this scenario CMDA could be used to examine the student and chatbot tutor relationship.  This could be used to grow the chatbots learning, and identify possible relationships created between human and AI interaction.  Now I have identified yet another thing I want to build and research!

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Reflection on what I have learned

I entered a qualitative research class with no idea what this entailed. I did not know how much qualitative descriptive data could add value to knowledge construction. Descriptive data can be viewed as not offering scientific results, and not be taken as seriously. When in fact it adds more meaning to data since it adds context. Conducting research with rigor will result in more trustworthy findings, and get my study taken more seriously. Initially thinking about the research that I want to conduct for my dissertation, I really did not know where to begin.  It is kind of exciting to go from curious to seeing a plan begin to formulate.  I know I have just skimmed the surface and am excited to learn more.

What I need to understand further

In my area of research constructivism appears to be more prevalent, which varies from my cognitivist views.  I will continue to look for research that associates my technical content and gamification interests with the cognitive paradigm. In working on my research framework, I realized I needed to learn more about data analysis methods. Although I have worked with some analysis methods; I am still learning how to determine the right process for analyzing my data.  In addition, I need to learn more about quantitative methodologies.  I have come so far this semester, and I believe by the end of summer school a lot of this will be clearer to me. Then enlightenment will bring more questions.

What next?

I have rewritten my framework five times now, even with that I view the current version as a draft that will require more work.  As I learn more, I will add to it and update it.  I have read a lot of literature this semester, or so I thought.  In the past I found more quantitative examples and didn’t give any thought to finding qualitative examples.  I found some this semester but need to dig deeper. Also, I have not purposefully searched for examples that use both qualitative and quantitative. More literature searches!

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Finding truth in research

The great digital age has also brought to light the rapid growth of fake news.  Wrong information can quickly travel to every web browser for consumption and reaction by those who wish to believe. We would expect the bar to be set a little higher for research, unfortunately it can be riddled with bias, personal opinion, and at times lacking in diligence. 

Quantitative research may appear to have the advantage just by the type of data that is generated.  The cold hard bottom line appears to be trustworthy, or at least solid enough to make a case for a particular position.  Of course, we need to know how the researchers bias was inserted in collection and analysis of this data.  Which still requires additional efforts to determine the trustworthiness.

Regardless of quantitative or qualitative research a few questions need to be answered to determine if the research has any potential of truth. 

Does this research sound logical?

A little common sense goes a long way.  An empirical study details methodologies and tools, as well as the handling and analysis of all collected data.  If this information isn’t noted it is difficult to trust any points the researcher makes.

The context should be logical. The research challenge and approach should be in the same context as the findings.  We can’t cut the puzzle pieces to fit, instead the puzzle should be assembled and looked at as it exists.

Correlations should also be logical.  For example, we could say there was a worldwide increase in jellybean sales when the coronavirus became a pandemic. Can we draw the conclusion that jellybeans create pandemics?  Not really, there might be another reason for high jellybean sales, like Easter.  Any research that makes erroneous or spurious correlations to make their point, lacks truth.

Did the researcher note credible resources? 

Most journals post how many times a paper has been cited and downloaded.  This can add some level of credibility; however, this should be put into a realistic perspective.  Newer research might be credible but obviously won’t be cited as much as older research, since it didn’t exist.

Being new to academic research I wouldn’t read a name or study and know if a true expert is being cited.  On my first literature review I found papers that noted other studies that I had found in my search.  In my limited experience this created a level of credibility for both the paper citing and the paper cited.

What evidence is there of validity? 

In looking at empirical evidence there should be an actual measurement with significance to back up any findings. For example, I have found a lot of gamification research noting the need to measure how working memory is influenced by game play.  Many researchers even elude to successfully finding how the working memory is influenced, even though there was no measure taken.  First, this finding can’t be trusted, since there was no data to support it.  Second, this study loses credibility since findings were made on opinions and wishes instead of by measurement.

It is easy to imagine how this could happen, a researcher would not put the time into a particular topic if they didn’t have an opinion or outcome they wanted to find. Add this passion to corporate partnerships. When a business entity monetizes research, they want to draw conclusions that will promote their stance.  The bottom line is findings should reflect the actual data that was gathered, with the context it was intended.

Can the research be repeated?

The research should detail measurement tools and methodologies that can be used to repeat the study.  Being able to repeat the research with the same or similar findings shows validity. However, different findings shouldn’t completely discredit the initial research.  Any repeating studies require scrutiny to determine similar and differing aspects from the original study, as well as overall validity.

This post is more of a summation of what I have observed, experienced, and learned so far. I believe I will revisit this topic and edit over time.

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Learning approach

Initial thoughts about how I would address different learning approaches had me dissecting various pieces to build a hybrid model.  Then I started to consider what my personal learning theory really was, and how I got to this point.

Personal Learning Theory

Origins of my personal learning theory stem from academic work and work experience, which incorporate more of a cognitivist point of view.  Every instructional design student has heard, read and thought about Gagne’s nine levels of learning at some point. It is a common practice for instructional designers to build learning objectives based on Bloom’s taxonomy.  We all have the verbs, organized into the cognitive domains of learning, saved on our computers.  A proper grouping of learning objectives must cover the range of Bloom’s cognitive domains.

Cognitivist’s believe the learning happens in how the brain processes information. External stimuli are received in the working memory.  This stimuli have approximately 6-9 seconds to attach to existing information.  This process will build on previous information and be stored for retrieval later.  Bits of new information may transfer to long term memory; the rest of the information is purged. 

The core of my research is based on a belief that the manner in which we receive information can influence how we process it.  Can content be delivered in a way that is easier for the working memory to process and offer a higher likelihood of transfer?  Can the presentation of content improve how we transform information into knowledge and disseminate that knowledge to new settings?

Applying different theoretical models

This brings me back to the question; if I had to use an incompatible research method how would I approach it?  The approach would depend on the type of content and audience.

Behaviorist’s see learning more as a teacher-centered, passive event. A teacher-controlled learning experience is more difficult to personalize and apply to new settings. Perhaps this theory can be applied in new job skill training, where it only takes a quick demonstration.  Then the learner would begin using those skills regularly and develop an expertise on their own.

Constructivist’s believe new ideas are derived from past experiences. This student-centered approach offers a way for learners to challenge information and find new applications.  It is appropriate for veteran learners; however, a novice does not have the experiences to draw from.

In trying to consider other approaches I tend to wonder what activity is taking place in the brain.  Is the working memory overwhelmed or underwhelmed with these approaches? 

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Potential ethical concerns and bias in my own research.

Ethics is not only institutional review boards, code of conduct, and laws, it can also be my own bias. Initial thoughts about personal bias leads me to the outcomes I want to find in my research.  I want to show that gamification can improve working memory processing.  Although many studies mention gamification and cognitive function there is very little empirical data.  Anything I contribute to this body of research would just be a steppingstone, but still exciting to uncover. It would be very easy to design survey questions that led participants into showing significant success.  I need to account for the potential of my bias in the design of my research.  All measurement questions need to be carefully worded as to avoid response bias.  In addition, the design needs to include a way to self-check and make sure my research is trustworthy.

After further study and the class discussion I realize I could encounter additional ethical concerns.  First, the researcher-participant relationship. Colleagues will be solicited to volunteer participation. This can lead to participants responding to what they believe are my wishes.   Since the research is not measuring individuals, but instead the success of the gamification, it would be possible to incorporate anonymous data collection.   This would make participants comfortable to respond freely without worry of affecting our working relationship.  The second concern is this will be design-based research.  At this point it appears I will be designing the gamification module that will be used in my research.  Is this a concern or an asset? In qualitative research the researcher is the tool used.  This should mean that all knowledge, experience, and even bias are valuable elements of the research process.  So, having an intimate knowledge of design and development of the gamified module should be an asset. As pointed out by Anderson & Shattuck (2012) “we argue that this inside knowledge adds as much as it detracts from the research.” (p18) Unfortunately an industry of exports might not agree with this perspective and find that my results are not trustworthy.  The research methodology should include a means of self-check to make sure it is staying true to finding truth.  Although my expertise can be an asset, it is important to incorporate a process that will let the gathered data light the path to the actual findings.

It is not uncommon for me to learn something and change trajectory very easily.  In qualitative research my challenge is that line between staying focused on goals and letting the research evolve through reciprocal transformation.  For this I need to establish distinct goals and logically disseminate them in order to redirect into new more progressive goals. Stay tuned as I figure out how to do this!  

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A deeper look at qualitative research

I have to admit I am still processing a lot of information, coupled with internet research. I am not prepared to apply but am starting to organize and make sense of some concepts.

Qualitative research pursues a deeper understanding of individual and group experiences.  The detailed descriptive nature goes beyond statistics to draw meaning from the natural context.  This approach adds value to knowledge construction since it can address the how and why.  Since research cannot be generalized with just data the researcher must be in the contextual setting to perform the study. The researcher does not sit in a hierarchical power, instead they sit more level with participants.

Since the information collected is related to a participant’s experience, and the researcher is so interactive with the study setting, it is easy for a researcher to insert their own opinion or experiences into the information collected.  Frequent self-assessments should be part of the study design.  This allows the researcher to determine if they are inserting personal experience or remaining neutral. A researcher should take more of an inquiry stance, and positionality should be taken into consideration in the methodology.  A vital element to a qualitative study is collaboration.  A researcher must engage in dialog with participants, associates, and advisors. Rigorous study design should include complex and contextual research questions, a responsive design with systematic data collection, an understanding of the context and individuals in that context, and always address study limitations. The level of detail is determined on a case-by-case basis, as well as by the approach.

Research Approach

This is not an exhaustive of qualitative approaches, but merely examples.

Phenomenological research looks at a real-life experience of groups and individuals in a community. A goal is to describe or give meaning to the phenomenon that was experienced.  Participants are observed and interviewed to determine what was actually experienced and the context in which it was experienced. For example, a study of individual activities in a specific scenario, then taking that further with how those activities affected the relationship between individuals. How did each individual’s perspective shape their reaction and dictate how they worked together.  Beyond the human element uncontrollable elements that occur in the environment can add perspective.

Ethnographic research puts the researcher in the setting that they are studying.  They are immersed into the environment as a participant might be, allowing them to observe and interact with participants from the vantage point of a participant. Initial methodology stages require identifying the problem, theoretical research, developing the questions that need to be answered and designing the study. The ethnographic approach can be applied in these earlier stages to identify possible phenomena, and aid in the design of the study. 

Historical qualitative research studies previous events to interpret and give meaning.  This meaning can be applied to current practices and events.  For example, identifying developmental stages of age group, educational levels, and personal characteristics.  This is applied to individuals or events that are being studied to add context to the information. 

Qualitative vs Quantitative

At this early stage of learning about qualitative research it appears to be a compliment to quantitative.  The statistical outcomes that can be determined in quantitative can be verified by qualitative methodologies.   That extra contextual detail would make quantitative data appear more trustworthy.  Of course, the decision to apply a mixed-method would depend on the study.

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What is qualitative research?

It is safe to say I enter this qualitative research class without a clear-cut idea of what it actually is.  Before my current job I would stop after the period with no idea of how-to breakdown the definition.  After developing data analytics training content, although I am still a novice, I do have some basis.  I know that qualitative data are values that can’t be measured numerically but are described through language.  This encompasses ordinal data which is a fixed ranking with an indeterminate distance between values, and nominal data which has distinguishable values but can’t be put in order.  Although this is not exactly a definition for qualitative research it does possess the same idea.

My definition is slightly adjusted after spending a little time with the textbook.  Qualitative research is the pursuit to understand varying perspectives and experiences of the people being studied, to give meaning and identify phenomena.  It isn’t systematic and can’t be generalized with data.  Instead it requires observation in natural settings, context of the challenge being pursued and a neutral position.

I am eager to learn more about qualitative research processes, since it appears to be an approach that fits my research goals.  Being a person that does not bode well with structure it is exciting to see a scientific process that can evaluate contextual details that fall outside of the box.

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