My Dissertation Abstract on MMORPGs to Improve ESL Skills

A Massively Multiplayer Online Role-Playing Game with Language Learning Strategic Activities to Improve English Grammar, Listening, Reading, and Vocabulary

Brightly colored winged-ferry is learning about a quest from a farmer in his field.
Example of roleplay in EverQuestII

This mixed-methods-collective-case-study focused on the use of an online videogame combined with second language acquisition (SLA) strategic gameplay to improve English language learners’ (ELLs) grammar, listening, reading, and vocabulary. Its purpose was to determine whether a noneducational, massively, multiplayer, online, role-playing game (MMORPG) had educational merit as an extracurricular activity for ELLs when combined with the following gaming activities to promote SLA: voice and text-based chats, forming alliances, and creating a virtual social identity.

The design included 15 participants who received 25 hours of weekly English language instruction in reading, writing, grammar, and oral skills for an eight-week term at school. For the treatment group, EverQuest® II (2016) was prescribed with the SLA optimizing strategic gameplay for four hours a week for a month after school. The control group did not receive the treatment.

The Cambridge Michigan Language Assessment (CaMLA) pretest-posttest composite mean gain scores were used to assess the participants’ grammar, listening, reading, and vocabulary performance. At end of term, the control group outperformed the treatment group on the CaMLA by 1.7 mean gain score units.

To determine vocabulary acquisition from gameplay, I developed a vocabulary pretest-posttest based on frequently occurring words from the treatment group participants’ game chat logs. The treatment group learned, on average, 15 new words representing a 30% increase on the gameplay vocabulary test.

No correlations were found between prior gaming experience and attitude toward gaming for SLA or between prior gaming experience and ESL skill performance on the CaMLA. Due to the small sample size and nonrandom assignment, this study lacked the rigor and statistical power to make valid and reliable quantitative claims of the findings. Therefore, a collective case study and mixed methods were used to corroborate and augment findings. Four impact profiles of extreme cases are provided. Emergent themes on gaming and language learning gleaned from participants were as follows: most participants had a positive attitude toward videogame play for SLA, most treatment group participants disliked the prescribed SLA strategic gameplay features and activities, and most participants preferred not to play videogames after school due to other priorities.


This dissertation is available on ProQuest.

Rogers, S., Johnson, B., Van Eck, R., Van Haneghan, J. & Martin, S. (2017). A MMORPG with Language Learning Strategic Activities to Improve English Grammar, Listening, Reading, and Vocabulary. In P. Resta & S. Smith (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2017 (pp. 451-463). Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).

How People Learn a Second Language

(Excerpted from my dissertation.)

Learning a second language is an arduous task. Most scholars would agree that it requires a lot of practice (Krashen, 1982; Nation, 2014), language activities that are embedded in realistic tasks (i.e., communicative approach) (Hymes, 1972; McFarlane, Sparrowhawk, & Heald, 2002), plasticity of the brain (Pinker & Bloom, 1990; Ward, 2010), and high levels of motivation (Crystal, 2010; Gardner, 1985). Here are the five stages of second language (L2) learning: preproduction, early production, speech emergence, intermediate fluency, and advanced fluency (Krashen & Terrell, 1983). Progress through these stages depends on level of formal education, family background, time spent in an English-speaking country, and many other variables.

For young children, oral language and literacy development should include support in their native language, sufficient time and support, developmentally and culturally appropriate material, a balanced and meaningful literacy program, and reliable, ongoing, and valid assessments (TESOL, 2010a). For adults, more specialized vocabulary and education on the sociocultural dimensions for the workplace or academic setting are required (TESOL, 2010b). Otherwise, adult L2 instruction is like that of young children, as noted in the vision and action agenda of the National Literacy Summit (2000). For example, they propose that adult learners also have access to native language or bilingual texts and instruction that is based on meaningful contexts.

There’s some disagreement as to the developmental stages of SLA, but most agree that the initial stage includes a silent period in which you understand some of the L2 but may not be able to produce it (Granger, 2004). Scholars disagree as to whether there is a critical period (cut-off time) for learning a second language with native-like fluency (Crystal, 2010). For instance, cognitive neuroscientists prefer the term sensitive period to refer to the limited window of time to learn due to evidence supporting the possibility of extended learning (Ward, 2010).

I agree with Pinker and Bloom’s (1990) idea that the critical period varies with maturation and plasticity of the brain due to natural selection. Hurford (1991), in his evolutionary model, referred to language learning past the critical age as the natural selection pressures activating the trait.  These pressures affect adults who come from around the world with the hope of learning English in order to attend an American university. One way to affect the plasticity of the brain is to play video games. Current research on the brain and its behavior indicate that playing highly arousing, reward-based video games activates brain plasticity (Kilgard & Merzenich, 1998).

Numerous factors affect learning ESL. For one, learning English takes a long time. For beginners, basic interpersonal communication skills can take two years to learn, while cognitive academic language proficiency can take five to seven years (Cummins, 2008). Influential factors include, but are not limited to, native language (L1) writing system, age exposed to English, cognitive ability, and exposure to other languages (National Literacy Summit, 2000). Another important factor is gender (i.e., female, male, other), which is influenced by the gender of the teacher, strategy use (Kiram, Sulaiman, Swanto, & Din, 2014), and conventional norms (Oxford & Nyikos, 1989). There’s no conclusive evidence that one gender is better at learning a L2. Oxford and Nyikos (1989) posit that it has more to do with strategy preferences and conventional norms.

References

Crystal, D. (Ed.). (2010). The Cambridge Encyclopedia of Language, 3rd ed. New York, NY: Cambridge University Press.

Cummins, J. (2008). BICS and CALP: Empirical and theoretical status of distinction. In B. Street & N. H. Hornberger (Eds.), Encyclopedia of Language and Education, Volume 2: Literacy (2nd ed., pp. 71-83). New York, NY: Springer Science + Business Media LLC.

Gardner, R. C. (1985). Social psychology and second language learning: The role of attitudes and motivation.  London, England: Edward Arnold (Publishers) Ltd.

Granger, C. A. (2004). Silence in second language learning: A psychoanalytical reading. Tonawanda, NY: Multilingual Matters, Ltd.

Hurford, J. R. (1991). The evolution of critical period for language acquisition. Cognition, 40, 159–201. doi:10.1016/0010-0277(91)90024-X

Hymes, D. (1972). Models on the interaction of language and social life. In J. J. Gumperz & D. Hymes (Eds.) Directions in sociolinguistics: The ethnography of communication (pp. 35-71). New York, NY: Holt, Rinehart, and Winston.

Kilgard, M. P., & Merzenich, M. M. (1998). Cortical map reorganization enabled by nucleus basalis activity. Science, 279, 1714-1718.

Kiram, J. J., Sulaiman, J., Swanto, S., & Din, W. A. (2014). The relationship between English language learning strategies and gender among pre-university students: An overview of UMS. Proceedings of the 3rd International Conference on Mathematical Sciences, Vol. 1602 (pp. 502-507). Kuala Lumpur, Malaysia: AIP Publishing LLC. doi:10.1063/1.4882532

Krashen, S. (1982). Principles and practices in second language acquisition.  Oxford, England: Pergamon Press.

Krashen, S. D., & Terrell, T. D. (1983). The natural approach: Language acquisition in the classroom. London, England: Prentice Hall Europe.

McFarlane, A., Sparrowhawk, A., & Heald, Y. (2002). Report on the educational use of games. Cambridge, England: TEEM.

Nation, P. (2014). What do you need to know to learn a foreign language? School of Linguistics and Applied Language Studies.  Victoria University of Wellington, New Zealand. Retrieved from http://www.victoria.ac.nz/lals/about/staff/publications/paul-nation/foreign-language_1125.pdf

National Literacy Summit. (2000). Adult ESL language and literacy instruction: A vision and action agenda for the 21st century. Office of Vocational and Adult Education. Washington, DC: U.S. Department of Education.

Oxford, R., & Nyikos, M. (1989). Variables affecting choice of language learning strategies by university students. The Modern Language Journal, 73(3), 291-300. doi:10.1111/j.1540-4781.1989.tb06367.x

Pinker, S., & Bloom, P. (1990). Natural language and natural selection. Behavior and Brain Sciences, 13, 707–784. doi:10.1017/s0140525x00081061

Teachers of English to Speakers of Other Languages. (2010a). Position paper on language and literacy development for young English language learners. Washington, DC: TESOL International Association. Retrieved from https://www.tesol.org/advance-the-field/position-statements

Teachers of English to Speakers of Other Languages. (2010b). Position statement on adult English as a second or additional language program. Washington, DC: TESOL International Association. Retrieved from https://www.tesol.org/advance-the-field/position-statements

Ward, J. (2010). The student’s guide to cognitive neuroscience. New York, NY: Psychological Press.

Goals of Research Study on MMORPGs + SLA Strategies

This summer, I started my research study for my dissertation on massively multiplayer online role-playing games (MMORPGs) combined with second language acquisition (SLA) optimizing activities.  I want to find out if free, commercial video games, MMORPGs in particular, are useful in helping English language learners (ELLs) acquire English skills.  Could MMORPGs be used to supplement language programs or personal learning agendas?  I’ll be using EverQuest II emphasizing language interactions and social identity (use of chat log, joining guilds, and character development), as an after school add-on in a mixed-methods-collective-case-study with nonequivalent comparison group design.

In my literature review and my previous case study on gaming and language learning,  ELLs self-reported that they learn English from playing video games.   Also, researchers on this topic are reporting positive gains for ELLs in vocabulary and language skills (reading, writing, listening, and speaking). My dissertation study focuses on these same skills, as well as student attitude toward gaming as a language learning tool and impact of prior gaming experience.

The goal of my study is to foster ELLs’ communicative competence—no matter their locale or socioeconomic situation.  Free role-play gaming (EQII provides 91 levels of free play) can provide opportunities to access authentic language learning environments for experiential learning.  MMORPGs challenge ELLs linguistically and provide accessible themes and embedded support systems.  Literature on gaming indicates gamers practice information literacy skills (seeking & disseminating information), collaboration, problem-solving, and decision-making through meaningful and relevant tasks.

I’ll keep you posted on my progress and findings on this blog.

Where Learning Happens

Young boy riding a wave
My Godchild Surfing (Photo source: Ed Compo)

During the flow of a task, at the edge of our zone of proximal development (ZPD), via our selective attention, rehearsal, and metacognition is where learning happens.  I acknowledge that this description short shrifts other important cognitive and behavioral learning processes; nevertheless, these are what I recognize as most important in creating an optimal learning experience. To be certain, many other constructs come into play such as ability, attitude, emotion, motivation, and personality.

Csikszentmihalyi’s (1990) flow theory describes the conditions for flow.  It occurs when there are rules, goals, feedback, and potential for participant control. His flow theory is not specific to learning, but rather generic to all of life’s activities. He described flow as an optimal experience; I translate that to “being in the zone”, which comes to us from popular culture (not the ZPD). In reading his work, I saw similarities to learning in his descriptions of flow in how it motivates one to higher levels of performance. For example, for an activity to engender enjoyment, it should provide manageable tasks, deep concentration, clear goals, immediate feedback, effortless involvement, learner autonomy, metamorphosis of self, and suspension of time. As an instructional designer, I want to utilize these aspects of flow to create optimal learning experiences.

Vygotsky’s (1978) proposed that learning takes place at the edge of one’s understanding with the help of others or a support system. This is known as the ZPD. This means that learning will not take place if the activity is too easy or too difficult. Csikszentmihalyi also described flow occurring for activities within a channel with just the right type of challenge to match a person’s skills. This channel exists somewhere between anxiety and boredom. Educators understand the need for differentiated instruction to meet each individual learner’s needs, but the reality of trying to make this happen in a classroom of diverse learners is almost impossible to do all of the time. Grouping according to ability is a solution but can cause equity issues if overdone. Computer-adaptive software programs, peer mentoring, cross-age tutoring, well-designed educational games, and pull-out programs for gifted or remediation are some solutions to providing the ZPD for our learners.

Self-regulation processes include rehearsal, selection of important information, and metacognitive strategies. Self-regulation aids working memory by stretching the time the information is held in storage, as well as enhancing transfer to and retrieval from long-term memory. A helpful example of self-regulation would be self-directed speech. Students might not think this is helpful, so an educator should model this behavior or otherwise teach it explicitly. Other useful learning strategies specific to self-regulation are mnemonics, reciprocal teaching, and reflection (written, verbal, or artistic formats).

Where do you think learning occurs? I’d love to hear your thoughts on this topic.

Sandra Rogers

References

Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY: Harper & Row.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

The Neuroscience of Learning

Neuroscience has the potential to prove and disprove existing educational learning theories, as well as identify learning disabilities. It will eventually lead to new discoveries and clearer explanations about the internal processes of the brain/mind. Hopefully, this information will make its way into educational textbooks and school curriculum. It already has determined many specific functions of the brain and aspects of human memory from research experiments using electrodes, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). For example, from the use of implanted electrodes in rats, neuroscientists identified place cells (neurons) that respond to a specific place from a collection of neurons (schemata) when needed (Ward, 2010).

Neuroscience has determined specific learning activities directly related to components of the brain. Neuroscientists are able to measure neuronal activity by observing the spiking rate of neurons as they code information. For example, the hippocampus stores contextual details for recall in a spatial map of the environment (Ward). This was discovered in a research study that planted electrodes in rats that maneuvered a maze; these rats’ neurons exhibited a high spiking rate only when they were in a particular location (O’Keefe, 1976). Later, in a study of humans that maneuvered in a virtual environment, it was determined that humans have place cells that are lateralized to a particular region of the hippocampus (Hartley, Maguire, Spears, & Burgess, 2003). The implications from this research finding suggest that it’s important for learners to discover the routes themselves in order to store this information; otherwise, it may not become a part of the spatial map if provided directly from the instructor.

Another study related to learning and cognition identified the basal ganglia as being responsible for regulating motor skills and skill learning (Ward). This was found through disorders of the basal ganglia. For example, individuals with Parkinson’s disease have damage to the basal ganglia structures and subsequent poverty of movement (hypokinetic). Neuroscience is helping better understand neurodegenerative disorders like Parkinson, but it still has not been able to solve them all.

Moreover, neuroscientists used fMRI to identify mirror neurons in monkeys. These neurons respond specifically to precise actions that are goal-directed but not to mimicked actions without an object (Ward). The neurons were even sensitive to the direction of rotation in mirroring an action. A study with infants showed similar imitation processes that are goal-directed more so than action-oriented. This data was collected from observation, not with the use of fMRI. These studies indicate that the act of imitation requires deeper cognitive processing than mimicry. Neuroscientists are investigating relations with mirror neurons and mirror systems such as empathy. These mirror systems are “…neural resources that disregard the distinction between self and others (Ward).”

There are many limitations to collecting data for neuroscience. For example, it’s difficult for young children to keep still under a scanner, and this disrupts the MR signal. Children are also unlikely to tolerate electrodes from an EEG. Bruning, Schraw, and Norby (2011) noted that even though fMRI shows activity in particular parts of the brain in correlation to specific mental activities, it really does not explain why or how. Additionally, the medical ethics of research on human subjects limits some of the advances of neuroscience. There is also a political debate on the use of animals as subjects of research studies. 

References

Bruning, R. H., Schraw, G. J., & Norby, M. M. (2011). Cognitive psychology and instruction. New York, NY: Pearson.

Hartley, T., Maguire, E. A., Spears, H. J., & Burgess, N. (2003). The well-worn route and the path less travelled: Distinct neural base of route following and wayfinding in humans. Neuron, 37, 877-888.

O’Keefe, J. (1976). Place units in the hippocampus of the freely moving rat. Experimental Neurology, 51, 78-109.

Ward, J. (2010). The student’s guide to cognitive neuroscience. New York, NY: Psychological Press.

Focus on the Process to Support the Growth Mindset of Students

Silhouette of head with different objects floating overhead

Dweck (2009) identified students’ beliefs about learning as their mindsets. Those who underestimate their ability to learn may have a fixed mindset, while those who believe that they can learn by establishing attainable goals and applying effort to learn have a growth mindset. Students with a growth mindset want to know the right answer. They want to be corrected; their ego isn’t tied to learning. They don’t mind revealing what they do not know. They understand that learning takes effort, and they enjoy it. Those with a fixed mindset don’t pay attention to corrective feedback; they don’t want to put forth effort to learn. Instead, they believe that learning shouldn’t take any effort because it’s tied to their intelligence. It shouldn’t be difficult if they’re intelligent; their ego influences how they learn.

It would be helpful for educators to explain the difference between the two mindsets to students and share the research findings. Perhaps students could use a learning style inventory to understand their mindset. Then they could reflect on how to make changes (self-regulate) to a growth mindset if they fall into the fixed mindset category. More importantly, educators need to learn how to provide feedback on student performance so as not to endanger a learner’s growth mindset. For example, praising a student for being smart doesn’t build their self-esteem. Instead, students must acquire self-esteem from their own effort and from overcoming struggles. Therefore, educators should praise persistence, acknowledge struggles, and identify students’ selection of challenging material/tasks. Focus on the process not the product when providing feedback.

Whatever mindset a person has will mold their motivation to learn (Dweck). A person’s personal belief of their ability to complete a task is explained in the the self-determination theory posited by Deci and Ryan. According to Deci, this theory states that personal control and autonomy (willingness, volition, endorsement of activity) affect your motivation to learn.  There is intrinsic and extrinsic motivation. Deci explained how extrinsic motivation can hinder the motivation to learn. For example, if you pay students for something they already enjoy doing intrinsically, this could cause them to rely on the extrinsic payment. If the extrinsic reward is removed, the student may become unmotivated to do the same task. This is because with extrinsic rewards, the learner does not maintain control nor autonomy of their learning. The extrinsic motivation is coerced. However, Deci explained how some extrinsically motivating events can become internalized as intrinsic. For example, helping the teacher with cleaning the classroom to earn a reward becomes something the student realizes is important for the good of the class.

Deci, E. What is self-determination theory? [Presentation]. Retrieved from Social PsyClips http://vimeo.com/30754832

Dweck, C. (2009). Developing Growth Mindsets: How Praise Can Harm, and How To Use it Well. [Presentation]. Paper presented at the Scottish Learning Festival, Glasgow. Retrieved from http://www.educationscotland.gov.uk/video/c/video_tcm4565678.asp
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This article was written by Sandra Rogers

Why I Think Non-violent Video Games Are a Valuable Learning Environment

Students wearing decorated boxes on their heads and hip to  look like characters from the Minecraft video game
Students in Minecraft Costumes at FIRST Robotics Competition

Gee’s (2007) description of semiotic domains reminds me of what my language peers refer to as multiple literacies; that’s the literacy required to perform a task beyond reading, writing, and arithmetic.  Semiotic domain refers to the ability to detect the signs, symbols, merit, value, and language of a particular activity in order to function properly within it. For example, children who play video games are learning the semiotic domain of that particular game environment.  If they’re playing Minecraft, then they’ll learn to appreciate their physical surroundings, system alerts, personal alliances, and any help section embedded within the game.  In essence, the game’s affordances, and their role within it, become the semiotic domain that must be learned in order for the learner to be successful.

I don’t think that children should play violent video games for these same reasons.  Even though the Supreme Court declared no age-limit to graphically violent video games in 2011 (due to the lack of evidence in inciting violence among young players), I believe the semiotic domain of those violent actions become imprinted on the child.  Due to the potentially harmful activity, scientists cannot properly study this phenomenon.

Gee stated that video gaming offers important semiotic domains which include active problem-solving, critical thinking, and unique language functions (“design grammar”) in-world as an avatar and in real life as a gamer playing the game.  Additionally, the learner discovers how they would react in new situations; they can replay the situation to manipulate outcomes.  In this way, the learner is able to make corrective actions on their own or through resets by termination. We seldom get the opportunity to manipulate our outcomes in real life. These are a few of the reasons why I think that nonviolent gaming is a valuable learning domain.

When I taught preschool at the University of California’s laboratory elementary school, I encountered parents who disliked my use of the series called Rotten Ralph by Jack Gantos. It’s a story about an undisciplined cat that always gets into trouble.  I thought the book would make a nice counter match with the popular Clifford the Big Red Dog series by Norman Bridwell. Clifford causes trouble not because he’s undisciplined but rather because of his large size.  Hence, he was not really ever in trouble for misbehaving.  I liked how Rotten Ralph showed that even if you act badly, your family will still love you and want you around. Children need to know that there’s room for error in their development of knowledge about the world around them.  In a sense, gaming can provide that error-safe environment—a world of resets.

Children should participate fully in semiotic domains to produce virtual objects, create alliances, and develop new meanings.  In Minecraft, they can create Lego-like structures for their alliances (guilds) and learn to survive various physical threats to self and environmental threats to their structure(s). This affords the child the feeling of accomplishment. Children still learn about life and death but not in a graphically violent way. Play is beneficial for humans’ assimilation and accommodation throughout life.  Piaget first posited this in his theory of cognitive development in the 1950s, which stated that play and imitation are essential human strategies.  Nowadays, there’s little time during the school day for play. There is, however,  an emphasis in computer literacy and developing critical thinking.  Perhaps gaming could meet that demand and allow for playtime, too.

References

Gee, J. P. (2007). What video games have to teach us about learning and literacy (2nd ed.). New York, NY: Palgrave Macmillan.

What Educators Need to Know about Working Memory

 

Working memory is a process in the brain where meaning is constructed from information received and potential self-regulation of memory occurs. It also serves as a temporary storage device. Working memory is limited to the amount of information it can hold and the duration it can remember. According to Miller (1956), humans are capable of remembering only seven plus-or-minus two pieces of information in our memory at any given time without the help of learning strategies. If self-regulation of the information is not engaged, working memory is limited to three seconds duration in the auditory registers (Ward, 2010). Ward notes that young children’s ability to remember information is more stringent than that of adults. This age difference and the other limitations should be considered when designing and/or delivering instruction. For example, instruction of content should also include strategies to help students learn (e.g., mnemonics).

Baddeley and Hitch (1974; Baddeley, 1986) developed a model for working memory to explain the internal processing of information. Its main components are sensory register, working memory, and long-term memory. The subcomponents are an executive control system, an articulatory loop, and a visual-spatial sketchpad. The executive control system selects information, plans, and then transfers information to long-term memory. The articulatory loop consists of the auditory and articulatory processes such as rehearsal. The visual-spatial sketchpad consists of the visual and spatial processes, which can also include rehearsal. An important caveat for educators is that some learners don’t intrinsically know to select only the important information for long-term storage.  Therefore, it would be helpful for educators to preview documents and highlight key points prior to assigning the reading.

Numerous factors and self-regulatory processes affect working memory. Self-regulation processes include rehearsal, selection of important information, and metacognitive strategies (e.g., making it meaningful, organizing, visualization, and elaboration). Self-regulation aids working memory by stretching the time the information is held in storage, as well as enhancing transfer to and retrieval from long-term memory. A helpful example of self-regulation would be self-directed speech. Students might not think this is helpful, so an educator should model this behavior or otherwise teach it explicitly. The National Research Council (Bransford, Brown, and Cocking, 1999) defines metacognition as taking “the form of an internal conversation.”

Here are some factors that hinder working memory:

  1. construction of memory requires attribution and inference and therefore can cause distortions as to the correct source,
  2. articulatory suppression can cause forgetting of non-articulated information,
  3. physical impairments can cause faulty encoding of information,
  4. multitasking influences the depth of learning,
  5. merely trying to remember something can conflict with other memories (Ward); and
  6. cognitive overload can occur when information is presented with distracting enhancements like background music or elaborative fonts.

There are different types of memories: declarative (episodic and semantic) and non-declarative memory (implicit) (Ward). Episodic memory refers to a person’s personal events, whereas semantic memory refers to conceptual knowledge. Ward stated that episodic memory is stronger than semantic memory; therefore, it’s imperative to teach students metacognitive strategies for encoding conceptual knowledge into long-term memory. These strategies should be embedded in the curriculum after they’re presented through direct instruction.

Note: For more information on the information processing system as it relates to instructional design see my blog on The Basics.

References

Baddeley, A. D. (1986). Working memory: Theory and practice. London, England: Oxford University Press.

Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 8, pp. 47-90). San Diego, CA: Academic Press.

Bransford, J. D., Brown A. L., & Cocking R. R. (1999). How people learn: Brain, mind,experience, and school. Washington, DC: National Academy Press.

Miller, G. A. (1956). The magical number seven, plus-or-minus two: Some limits on ourcapacity for processing information. Psychological Review, 63, 81-97

Ward, J. (2010). The student’s guide to cognitive neuroscience. New York, NY: Psychological Press.

Instructional Design for Human Learning: The Basics

The information processing theory explains how humans perceive, internalize, and remember information. The Atkinson and Shriffin’s (1968) information processing model included three systems: sensory memory, short-term memory, and long-term memory. This was a linear process, which has since been replaced with the nonlinear working memory model (Baddeley & Hitch, 1974) and other connectionist processes that align with current cognitive neuroscience views of human learning. Instructional designers should focus on the following concepts of information processing to improve learning and retention: the importance of gaining students’ attention, the limitation to working memory, and how to reduce cognitive load.

First, paying attention to instruction is paramount to learning. Bruning, Schraw, and Norby (2011, p.15) define attention as “the mental energy used to perceive, think, and understand.” A person’s attention is limited, selective, but can be self-regulated. There are several distracters which compete for a person’s attention such as noise outside the classroom, unmet physiological needs (e.g., hunger), and psychological aspects (e.g., motivational factors). Therefore, students need to selectively focus on the key elements of the information to be learned. It’s important to explicitly tell students about the importance of attention and teach them how to focus in order for them to be successful. Bruning et al. (p. 35), refer to this as “managing their resources.” They also encourage us to help students transfer these strategies to other content, as this may not occur to them without prompting. As instructional designers, we’re trained to use Gagne’s (1985) nine events of instruction, the first of which is to gain the learner’s attention. Some of the various instructional strategies to achieve this goal are to manipulate the motion, size, intensity, novelty, and/or incongruity of the information.

Second, consider the limitations to working memory and embed metacognitive strategies to help students learn the content. According to Miller (1956), humans are capable of remembering only seven plus-or-minus two pieces of information in our memory at any given time without the help of learning strategies. Therefore, it’s imperative for educators and/or the instruction to provide students with memory strategies to expand this capability or otherwise limit the amount of information provided at any given time. A sampling of learning strategies include chunking, imagery, mnemonics, and rehearsal. Instructional designer should identify specific learning strategies to help students stretch their working memory according to the content, learning environment, and age-appropriateness.

Lastly, due to the competition on a learner’s attention and the limitations to working memory, consider reducing the cognitive load when designing lessons. The cognitive load theory is attributed to Baddeley’s working memory model. Theorists took his model a step further to explain the various intrinsic and extraneous demands on learning information (Sweller, Van Merriënboer, & Paas, 1998). Cognitive load refers to the amount of effort required to process information. For example, difficult information requires more effort due to its intrinsic structure. Extraneous demands refer to how the information is presented during instruction. Bruning et al., explained how intrinsic cognitive load is unalterable until you properly learn something, so that it becomes part of your schema. Instructional designers need to consider the complexity of the content, instructional environment, and the characteristics of the learners in order to avoid cognitive overload. Here are some tips:

  • slow the speed of delivery of complex concepts;
  • sequence tasks logically;
  • use a multimodal approach to delivery; and
  • segment tasks such as instructional videos in small chunks of time (e.g., five minutes).

References

Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 8, pp. 47-90). San Diego, CA: Academic Press.

Sweller, J., Van Merriënboer, J., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review10(3), 251–296. doi:10.1023/A:1022193728205