Educational Robotics and Constructionism (Papert)

Summary: Constructionism as a learning theory emphasizes student-centered discovery learning, and educators are currently expanding its reach to the field of educational robotics in order to engage students.

Originators and Key Contributors: Seymour Papert took Piaget’s theory of constructivism and adapted it into his theory of constructionism.

Keywords: constructivism, constructionism, learning theory, discovery learning, educational robotics, technology


Dopamine, Games, and Motivation

Summary: Dopamine plays a role in motivation, and this role is important to understand in the context of game design. Understanding how dopamine motivates can help game designers produce games that are interesting, effective, and ethical.

Originators and Key Contributors: Henry Chase and Luke Clark presented a study in 2010 that suggested that dopamine was not linked to pleasure as previously understood. By studying groups of gamblers, they found that release of dopamine occurred whether there was a stressful situation presented or a rewarding one[1]. In 2012, a team of Vanderbilt researchers published a study with influential repercussions on our understanding of dopamine and its relationship to motivation. They found a difference in dopamine’s effects based on which areas of the brain expressed higher levels of it[2].

Keywords: dopamine, motivation, addiction, game, reward


Uses and Gratification Theory

Summary: Uses and gratification theory (UGT) is an audience-centered approach that focuses on what people do with media, as opposed to what media does to people.

Originators and Key Contributors: Uses and gratification theory builds off of a history of communication theories and research. Jay Blumler and Denis McQuail laid the primary groundwork in 1969 with their categorization of audience motivations for watching political programs during the time of the 1964 election in the United Kingdom[1]. This eventually led them to develop UGT later on with their colleagues[2][3][4].

Keywords: gratification, media, audience, entertainment, mass media, communication


Gamification in Education

Summary: Gamification describes the process of applying game-related principles — particularly those relating to user experience and engagement — to non-game contexts such as education.

Originators and Key Contributors: In 1980, Thomas Malone published the study “What Makes Things to Learn: A Study of Intrinsically Motivating Computer Games.”[1] Later, in 2002, the Woodrow Wilson International Center for Scholars, based in Washington D.C., established the Serious Games Initiative to explore the application of game principles to public policy issues. From that initiative, gamification for education emerged and gradually evolved into a field of study. The term gamification was coined in 2003 by Nick Pelling[2][3]. Today, many game researchers including Katie Salen, founder of the Quest to Learn public school, Jane McGonigal, Director of Game Research and Development at the Institute for the Future, and Joey J. Lee, Director of the Games Research Lab at Teachers College, Columbia University, have extended serious advancements in the application of gamification (or “gameful thinking”) to educational contexts.

Keywords: gamification, education, learning, classroom, engagement, motivation


Game Reward Systems

Summary: The phrase game reward systems describes the structure of rewards and incentives in a game that inspire intrinsic motivation in the player while also offering extrinsic rewards. Game reward systems can be modeled in non-game environments, including personal and business environments, to provide positive motivation for individuals to change their behavior.

Originators and Key Contributors: Many theories on intrinsic motivation, sense of satisfaction, and other reward concepts have been developed that form the foundation for current thinking about game reward systems. In the 1930s, B. F. Skinner explored reward schedules with pigeons, and his findings have influenced the design of reward mechanisms both inside and outside of the field of game mechanics. In their paper Game Reward Systems: Gaming Experiences and Social Meanings (2011), Hao Wang and Chuen-Tsai Sun analyze the main structural features of reward systems within videogames that have relevance outside videogames as well[1].

Keywords: game, variable ratio, fixed ratio, reward, intrinsic motivation, extrinsic motivation


Online Collaborative Learning Theory (Harasim)

Summary: Online collaborative learning theory, or OCL, is a form of constructivist teaching that takes the form of instructor-led group learning online. In OCL, students are encouraged to collaboratively solve problems through discourse instead of memorizing correct answers. The teacher plays a crucial role as a facilitator as well as a member of the knowledge community under study.

Originators and Key Contributors:

Linda Harasim, professor at the School of Communication at Simon Fraser University in Vancouver, developed online collaborative learning theory (OCL) in 2012[1]from a theory originally called computer-mediated communication (CMC), or networked learning[2][3][4].

Keywords: collaborative learning, internet, virtual classroom, e-learning, discourse, constructivism


E-Learning Theory (Mayer, Sweller, Moreno)

E-learning theory consists of cognitive science principles that describe how electronic educational technology can be used and designed to promote effective learning.


The researchers started from an understanding of cognitive load theory to establish the set of principles that compose e-learning theory. Cognitive load theory refers to the amount of mental effort involved in working memory, and these amounts are categorized into three categories: germane, intrinsic, and extraneous[1].

Germane cognitive load describes the effort involved in understanding a task and accessing it or storing it in long-term memory (for example, seeing an essay topic and understanding what you are being asked to write about). Intrinsic cognitive load refers to effort involved in performing the task itself (actually writing the essay). Extraneous cognitive load is any effort imposed by the way that the task is delivered (having to find the correct essay topic on a page full of essay topics).

Key Concepts

Mayer, Moreno, Sweller, and their colleagues established e-learning design principles that are focused on minimizing extraneous cognitive load and introducing germane and intrinsic loads at user-appropriate levels[2][3][4][5][6]. These include the following empirically established principles:

Multimedia principle (also called the Multimedia Effect)

Using any two out of the combination of audio, visuals, and text promote deeper learning than using just one or all three.

Modality principle

Learning is more effective when visuals are accompanied by audio narration versus onscreen text. There are exceptions for when the learner is familiar with the content, is not a native speaker of the narration language, or when printed words are the only things presented on screen. Another exception to this is when the learner needs to use the material as reference and will be going back to the presentation repeatedly.

Coherence principle

The less that learners know about the presentation content, the more they will be distracted by unrelated content. Irrelevant video, music, graphics, etc. should be cut out to reduce cognitive load that might happen through learning unnecessary content. Learners with some prior knowledge, however, might have increased motivation and interest with unrelated content.

    Contiguity principle

    Learning is more effective when relevant information is presented closely together. Relevant text should be placed close to graphics, and feedback and responses should come closely to any answers that the learner gives.

    Segmenting principle

    More effective learning happens when learning is segmented into smaller chunks. Breaking down long lessons and passages into shorter ones helps promote deeper learning.

    Signaling principle

    Using arrows or circles, highlighting, and pausing in speech are all effective methods of signaling important aspects of the lesson. It is also effective to end a lesson segment after releasing important information.

    Learner control principle

    For most learners, being able to control the rate at which they learn helps them learn more effectively. Having just play and pause buttons can help more than having an array of controls (back, forward, play, pause). Advanced learners may benefit from having the lesson play automatically with the ability to pause when they choose.

    Personalization principle

    A tone that is more informal and conversational, conveying more of a social presence, helps promote deeper learning. Beginning learners may benefit from a more polite tone of voice, while learners with prior knowledge may benefit from a more direct tone of voice. Computer characters can help reinforce content by narrating the lesson, pointing out important features, or illustrating examples for the learner.

    Pre-training principle

    Introducing key content concepts and vocabulary before the lesson can aid deeper learning. This principle seems to apply more to low prior knowledge learners versus high prior knowledge learners.

    Redundancy principle

    Having graphics explained by both audio narration and on-screen text creates redundancy. The most effective method is to use either audio narration or on-screen text to accompany visuals.

    Expertise effect

    Instructional methods that are helpful to low prior knowledge learners may not be helpful at all, or may even be detrimental, to high prior knowledge learners.

Additional Resources and References



  1. Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational psychologist, 38(1), 43-52.
  2. Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions?.Educational psychologist, 32(1), 1-19.
  3. Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309-326.
  4. Low, R., & Sweller, J. (2005). The modality principle in multimedia learning.The Cambridge handbook of multimedia learning, 147, 158.
  5. Mayer, R. E. (2003). Elements of a science of e-learning. Journal of Educational Computing Research, 29(3), 297-313.
  6. Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. John Wiley & Sons.

Online Disinhibition Effect (Suler)

Summary: The online disinhibition effect describes the loosening of social restrictions and inhibitions that are normally present in face-to-face interactions that takes place in interactions on the Internet.

Originators and Key Contributors: In 2004, John Suler, professor of psychology at Rider University, published an article titled “The Online Disinhibition Effect,” which analyzed characteristics of internet interactions that contributed to this effect[1]. The term “online disinhibition effect” was already in use at the time.

Keywords: online, internet, anonymity, invisibility, imagination, disinhibition


Intrinsically motivating instruction (Malone)

Summary: Intrinsically motivating instruction takes place in computer gaming software when it provides players with choice around three key categories: challenge, curiosity, and fantasy.

Originators and Key Contributors: Thomas W. Malone

Keywords: challenge, choice, computer games, curiosity, fantasy, intrinsic motivation

Intrinsically Motivating Instruction

In trying to understand what made computer-based learning environments (CBLEs) fun and engaging, Dr. Thomas W. Malone studied computer games[1]. In doing so, Malone developed a theory of intrinsically motivating instruction. The three categories which comprise his theory are challenge, fantasy, and curiosity[2].

Challenge: Each challenge must have a series of goals, which can be personally meaningful to the player and/or may be generated by the game to keep the player engaged. The game provides the player feedback on progress toward the goal throughout the game play. Because the computer game’s outcome is uncertain, this keeps the player engaged and motivated. When a player is challenged and succeeds through the struggle, a player’s self-esteem can increase, as long as the computer game’s feedback is constructive and supports learning. An optimal challenge should be neither too difficult nor too easy.

Fantasy: Malone defines fantasy as the “mental images” the players create based on interacting with the environment. The most effective fantasies in computer games are those which are more fully integrated with the content to be learned (intrinsic). Incorporating intrinsic fantasies creates more engagement, which increases memory of the material, because they may satisfy players’ emotional needs and help them learn skills within a meaningful context. (An example that Malone describes is an Adventure game where players practice reading maps, writing instructions, and feeling excited, puzzled, and triumphant as they proceed through it.)

[sociallocker]Curiosity: Two types of curiosity are important to successful computer game creation—sensory and cognitive. Sensory curiosity is activated by the aesthetics of the game (its look, sounds, feedback, authentic creation of a world or event). Cognitive curiosity is activated by presenting opportunities for the player to better their knowledge.[/sociallocker]

When a computer game is designed based on this framework, players are more motivated to play and learn[3].


  1. Malone, T. W. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 5(4), 333-369.
  2. Malone, T. W., & Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. Aptitude, learning, and instruction, 3(1987), 223-253.
  3. Lepper, M. R., & Malone, T. W. (1987). Intrinsic motivation and instructional effectiveness in computer-based education. Aptitude, learning, and instruction, 3, 255-286.