Simulations, Games, and Learning

Where We Begin

Exploring games and education is inherently controversial. Games can seem uneducational; they are typically associated with play and childhood. Even the name implies that games are the opposite of work. Assertions that games must be used to make learning “fun” ignore the fact that students who are deeply engaged in learning consider it both fun and hard work. Most of us begin a discussion of games with some discomfort and with an incomplete experience base. For many educators, the term “game” conjures up a mental image of playing cards or a game like Jeopardy. These “casual games” are brief (five minutes to two hours) and simplistic. Today’s games are complex, take up to 100 hours, require collaboration with others, and involve developing values, insights, and new knowledge. They are immersive virtual worlds that are augmented by a more complex external environment that involves communities of practice, the buying and selling of game items, blogs, and developer communities. In many ways, games have become complex learning systems. It is hard to understand something without direct experience. Yet that is how many approach games in education. Most educators are neither game players nor game developers. How much of our skepticism about the educational value of games is tied to experience (or lack of experience)? If we had the same experience base as a 15-year-old game enthusiast, might we view games differently? If we were discussing “virtual worlds,” “synthetic worlds,” or “immersive multiuser environments,” would our mind set be different? Our own biases and experiences can influence the exploration of games in education. Although definitions vary, digital games provide visual information to one or more players, accept input from the player(s), and use a set of programmed rules. Unlike more traditional games, the rules are not described in an instruction manual; they are programmed into the code. The sensory interface and story adds emotional appeal, as well. Games should be thought of as a family of related items; they are not all alike—they are not designed for the same audiences, nor do they incorporate the same features of game play. Among the common categories of games are

 • adventure games, where the player moves through a virtual world,

• puzzle games, such as Tetris,

• role-playing games, where the player assumes the role of a person or creature, such as Dungeons and Dragons,

• strategy games, such as The Sims, where a player’s strategy drives the game,

 • sports games, such as golf or football, and

• first-person shooter games. 3 Games are now part of modern culture.

Not only are scholars beginning to study gaming as part of contemporary society, but an increasing number of degree programs have emerged. Preschool children play educational games to learn colours, numbers, and names. Virtually all children will have played video games by the time they graduate from high school.

Game play is common in college, as well. In a U.S. survey, 65 percent of respondents were regular or occasional game players. Games are part of their multitasking environment; students play games while visiting with friends, listening to music, or doing assignments (in observations, male students were frequently seen to have online games open alongside their assignments). Thirty percent of college students admit playing games in class. However, games aren’t just for youth; the average age of a game player is 30. In the United States, 50 percent of adults play games; one in five adults over 50 is a video gamer. Males and females play games about equally (55 percent are male; 43 percent are female). Perhaps the prevalence of games is why 63 percent of parents believe games are a positive part of children’s lives; nearly 60 percent of teachers in the United Kingdom are willing to use games in the classroom. Not to be forgotten is the gaming industry; it is sizable. Digital gaming is a $10 billion per year industry, projected to reach $29 billion by 2007. In 2004, nearly 250 million games were sold. Whether or not we play games, gaming has become part of our culture. But games are still evolving. Rather than their simpler predecessors, today’s games are coming to represent “distributed authentic professionalism,” meaning that players are learning how to be a professional—a solider, an astronaut, an entrepreneur, and so on. Knowledge and skills are built into the virtual characters, objects, and environments; the players must master the skills they don’t have as well as integrate their skills with those of the virtual characters and other players. These types of games distribute expertise among the virtual characters and the real-world players. More than just a game, they are networked communication systems with interactive chat, internal e-mail, and messaging. They also require the player to adopt a certain set of values and a particular world view which is connected to performing activities within a specific domain of knowledge. By the end of the game, the player has essentially experienced a profession.

Effective Learning Environments

Other papers (Shaffer et al. and NESTA Futurelab) describe how games can facilitate learning. It is important to emphasize that games and play may be effective learning environments, not because they are “fun” but because they are immersive, require the player to make frequent, important decisions, have clear goals, adapt to each player individually, and involve a social network. Games have many attributes detailed below that are associated with how people learn.

• Social. Games are often social environments, sometimes involving large distributed communities. “It is not the game play per se but the social life around the edge of the game that carries much of the richness in terms of the game’s meaning, its value, and its social and cultural impact.”

 • Research. When a new player enters a game, he or she must immediately recall prior learning, decide what new information is needed, and apply it to the new situation. Those who play digital games are often required to read and seek out new information to master the game.

• Problem solving. Knowing what information or techniques to apply in which situations enables greater success, specifically, problem solving. This often involves collective action through communities of practice.

• Transfer. Games require transfer of learning from other venues―life, school, and other games. Being able to see the connection and transfer existing learning to a unique situation is part of game play.

• Experiential. Games are inherently experiential. Those who play games engage multiple senses. For each action, there is a reaction. Feedback is swift. Hypotheses are tested, and users learn from the results.

 Most educators are familiar with the world-to-the-desktop interface that computers provide, enabling users to access resources, distant experts, collaborations, and communities of practice. The user “sits outside” the virtual world, but can access resources through it. An increasingly common interface—a critical one for games and immersive environments—might be called an Alice-in-Wonderland, multiuser virtual environment. Whether the technology involved is a computer or a handheld ubiquitous device, participants can interact with computer-based agents and artefacts, virtually. A key distinction is that the world-to-the-desktop interface is not psychologically immersive. Virtual environments and augmented realities cause a psychological sense of sensory and physical immersion resulting in one feeling “inside” an environment.

Experience and reflection are important parts of learning; an ideal learning environment allows the learner to alternate between being “inside” an environment (fostering situated learning) and being an outsider looking in (fostering insights gained from perspective). Active learning based on immersive experience (real or simulated) that includes frequent opportunities for reflection is both engaging and effective for a broad spectrum of students. Most multiplayer virtual environments used today are games.

These immersive environments use authentic contexts, activities, and assessment; they also involve mentoring and apprenticeships in communities of practice. The result is a powerful pedagogy that allows for immersion and intense, extended experiences with problems and contexts similar to the real world. It may not be the “game” that is effective for learning but the immersive multiplayer virtual environment in which it is set.

Immersive multiplayer virtual environments let players participate in new worlds, inhabiting roles that would otherwise be inaccessible to them. They allow people to think, act, and talk in new ways. Rather than relying on words and symbols, learners experience the virtual world. Players can experience the ways a particular discipline thinks about and solves problems, as a physicist, an astronaut, or a physician. By requiring one to become a member of the community (or guild) and to develop knowledge, skills, and values, novices are exposed to the ways professionals deal with problems, mirroring the practice of becoming an expert. “A large body of facts that resists out of context memorization and rote learning comes easily if learners are immersed in activities and experiences that use these facts for plans, goals, and purposes within a coherent domain of knowledge.”

Another critical element of games is the community that develops around them. Ideas are shared in these communities, group problem-definition and problem-solving occurs, as well as a good deal of socializing. In fact, the description of a game community mirrors closely the definition of an educational community of practice. The community has a culture of learning; everyone is involved in a collective effort of understanding. The expertise of members is diverse; members are valued for their contributions and helped to develop further as the group continually advances its collective knowledge and skills. The emphasis is on learning how to learn and sharing learning. “It is not necessary that each member assimilate everything that the community knows, but each should know who within the community has relevant expertise to address any problem.” Developing this skill is important personally and professionally, not just in the game world.

Games and Schools

Although games can be effective learning environments, not all games are effective, nor are all games educational. Similarly, not all games are good for all learners or for all learning outcomes. Games may remain on the side lines until rubrics and evaluation strategies are developed that assess a game’s value. “Faculty members need training to analyze, design, develop, implement, and evaluate digital game-based learning (DGBL). Staff members need training to support faculty during this process.”

How games are used is important as well. Simply using games may not be very effective; use is not synonymous with integration. In fact, use of one strategy is often assumed to replace another (for example, a game replacing face-to-face instructional time). What is more important is to consider how to add games to the educational tool set, blending them with other activities. Integration requires an understanding of the medium and its alignment with the subject, the instructional strategy, the student’s learning style, and intended outcomes. Integration of games into curricula is much more likely to be successful than mere game use.

There are a range of options for integrating games into education. Strategies include allowing students to create their own games or integrating commercial games into the curriculum. If games are integrated into the curriculum, it will be important to understand what types of games promote the desired learning outcome. For example:

• Card games promote memorization, concept matching, and pattern recognition

 • Jeopardy-style games encourage quick mobilization of facts, labels, and concrete concepts

 • Arcade-style games are good for improving speed of response, automaticity, and visual processing

• Adventure games are useful for promoting hypothesis testing and problem solving.

If games are integrated into the curriculum, strategies may go beyond game play. An alternative to playing a game is to ask students to critique a game. This allows students to explore not just the subject but how the game is structured. Since most games were not designed for educational purposes, it is not surprising that details may be missing or facts incorrect.

 Another strategy is to have students discover what is missing or incorrect in a game. Beyond selection of a game, educators must consider when and how to integrate a game into the curriculum or the class. Options include use as a

 • preinstructional strategy,

• coinstructional strategy (augmenting, illustrating, discussing), and

• postinstructional strategy (for assessment and synthesis).

Games may also be considered a part of the informal educational environment.

Implementation Issues

Among the most staggering game figures are their development costs, commonly reported in the tens of millions of dollars. It would be easy to assume that educators need to spend millions to develop educational games. Cost is often used to argue against the use of games in education. However, game engines are increasingly available, reducing the cost of game development. MIT, for example, has made its augmented reality game engines available to other developers. Rather than developing the software for the game, the developer simply overlays his or her scenario on a generic shell. In the last year, even developers of military simulations have seen their development costs drop as game development tool sets become more widely available.

Institutions must consider a host of implementation issues. For example:

• Are computer laboratories available where students can play games? Are they appropriately configured? Are they available for the extended hours that game play involves?

• Is the right equipment available, such as headphones, speakers, special consoles?

• Is support available for the game, both technically and in terms of game play?

• Are there instructional designers who can develop games?

 • Is gaming integrated into the curriculum or just added on?

Professional development and support is a significant implementation issue. “Everyone involved in the design, development, or implementation of digital game-based learning needs training on what DGBL is and how it is supported and implemented, institution-wide.” Students will need support for games, implying help desk personnel must be prepared for common questions, procedures, and technical issues. And, instructional or IT units may need assistance with licensing agreements and negotiating discounts. Using games or multiuser immersive virtual environments in education will require “unlearning” many unconscious beliefs, assumptions, and values about teaching and learning, as well as the structure of education. Unlearning requires higher levels of emotional and social support than traditional forms of staff development. Ideally, it should take place in distributed learning communities so learning occurs in context.

Today and Tomorrow

Most games that have been developed to date were not designed for educational purposes. Although they may educate, that is not their primary goal or their most important design feature. Moving forward, educators must hope for games based on learning theory and research. These future tools may not be games but rather massively multiplayer immersive worlds where learners develop epistemic frames and social networks.

Games are in an early stage of evolution. As we gain more experience, our adoption and adaptation of games will become increasingly sophisticated; we may find that the ultimate value of games does not mirror today’s uses.

ICT EDUCATION - a perspective view

Technology is omnipresent, touching almost every part of our lives, our communities, our homes. Yet most schools lag far behind when it comes to integrating technology into classroom learning. Many are just beginning to explore the true potential tech offers for teaching and learning. Properly used, technology will help students acquire the skills they need to survive in a complex, highly technological knowledge-based economy.

There was a time, not so long ago, when ‘education’ was primarily defined by the course books prescribed by the school boards and later, the universities. School ‘achievement’ comprised of the number of students who could assimilate the quantity of prescribed materials and extensively answer questions in the Board Examination. In the 21st century, the perception of ‘education’ has swung from a product or content driven approach to one that has now re-focused to achieve new curricular goals, that are process and information driven, supported by readily accessible Information and Communication Technology [ICT]. The latter is a necessary progression for all schools to prepare all students for the future through computer education classes that develop the requisite skills and inculcate knowledge about computers and technology.

The Government of India has approved a blueprint for the Digital India programme, which envisages all government services be delivered electronically by 2018. It will also provide high-speed internet as a core utility down to the gram panchayat level and a "cradle-to-grave digital identity unique, lifelong, online and authenticable". Therefore, the question that we need to answer is: Is the present day education preparing all students for such a future?

“In simple terms, digital equity means all students have adequate access to information and communications technologies for learning and for preparing for the future-regardless of socioeconomic status, physical disability, language, race, gender, or any other characteristics that have been linked with unequal treatment.” (Soloman, 2002)

We should constantly lay emphasis on making school education meaningful and relevant so that it acts as a powerful tool for human resource development. However, some sections of the student community need more help to gain an equitable access to such education which will give them the necessary edge, as they transition to college/university or the workforce. Here, the challenge is for schools to search the market to find affordable, quality hardware in sufficient quantities, explore options for easy and low-cost internet access to bridge the knowledge and skills-gap between those who ‘have’ and the ‘have-not’ [access to a computer at home].

Besides, ensuring digital equity also implies the capacity-building for school teachers at all levels, who would be the most important asset to ensure digital equity for all students. Besides, trained teachers would be able to bring in a more integrated /holistic approach to their lesson –planning and pedagogy through their effective and efficient use of technology.

Since, social and professional interactions now and in the future will require students to use technology in some form to enhance the quality of life. To become informed adults and citizens, it is only at school that all students, regardless of their background, can have the opportunity to learn how to use the computer, to conduct online research, surf the internet, learn to check if online information is legitimate, share and discuss with their peers and teachers through e-mail and networking, take responsibility for their learning and consequently, construct knowledge.

Digital natives can efficiently configure instruction to solve problems, complete assigned tasks confidently or even express their creativity is many forms, across the curriculum. Students can begin to create their own unique conceptual frameworks without feeling the constraint of the prescribed parameters of their course books or the teaching styles of their tutors. These skills are important life-skills.

Figure below depicts the academic discipline of Information Technology. The pillars of IT include programming, networking, human-computer interaction, databases, and web systems, built on a foundation of knowledge of the fundamentals of IT. Overarching the entire foundation and pillars are information assurance and security, and professionalism. While this figure does not depict all aspects of the IT discipline, it does help to describe the relation of the key components.

Effective Pedagogy

As with the term ‘pedagogy’, the term ‘effective’ is contested. The ultimate goal of any pedagogy is to develop student learning, and yet the Global Monitoring Report on quality (UNESCO) includes creative, emotional and social development as indicators of quality learning. In order to include a wide number of studies on pedagogy, the review has conceptualised ‘effective’ pedagogy as those teaching and learning activities which make some observable change in students, leading to greater engagement and understanding and/or a measureable impact on student learning. Implicit in these definitions is a starting point or baseline with which to contrast the observable change in behaviour or learning taking place as a result of a teacher’s pedagogy.

An alternative term we could have used is that of ‘quality’, referring not merely to school, national or international student examinations or assessments but also to the quality of the human interaction in the classroom through appropriate pedagogy. ‘Quality’, however, can be seen as looking at the relationship between school inputs, such as quantitative surveys of textbooks and other physical school resources and student achievement, but studies focusing on these range from showing ‘significant positive associations’ (Barrett et al., 2007, p.22) to others which state that ‘there are no clear and systematic relationships between key inputs and student performance’ (Hanushek 1995, p. 232, cited in Barrett et al., 2007).

“Educators are at the heart of the knowledge economy. Teachers in the twenty-first century are increasingly being understood as knowledge workers with the power to facilitate, motivate and collaborate … the potential impact of twenty-first century educators is unparalleled (Kalantzis and Harvey 2002, p. 9).”

TEACHING -LEARNING STRATEGY

As indicated in this section addresses the purpose of ‘curriculum as a process”. Several curriculum theorists [Stenhouse 1975] have suggested that a curriculum should include not only content, but also the means to transact that content. Hence a curriculum must provide principles for the development of a teaching strategy. Once the decision is made on what is worth teaching, psychology and pedagogy principles should guide us identify effective teaching-learning strategies [Kumar 2004]. This section recommends broad strategies on which specific teaching methods and lesson plans can be developed. These strategies are established to be effective and are suitable in the context of IT education. It is recommended that teachers and school implementers incorporate these strategies.

Inquiry-based learning

Inquiry-based learning [Barrett 2005; Olson, S. and Loucks 2000] is an approach in which students are actively engaged in the learning process by asking questions, interacting with the real world, and devising multiple methods to address the questions. Learners are guided by questions that lead to gathering of evidence, formulating explanations from the evidence and communicate and justify the explanations. The teacher plays the role of a cognitive guide and a facilitator in the process. Inquiry based learning is an effective way to realize the key feature of Thinking Skills.

There are different levels of inquiry-based learning. In some forms, the problem is suggested by the teacher and the students devise their procedure to solve the problem. For example, the teacher asks students to prepare a presentation on an unfamiliar topic, such as maintaining an aquarium or embedded applications of computers. Students first identify what they already know about the topic and what they need to find out. Then they gather the relevant information from various sources, and synthesize it to create the presentation. 

Learning via Real-world Context

Learning is most effective when it is situated in a real-life context [Bransford et al 1992]. It engages and challenges students to make connections between their environment and the formal curriculum. Making real world connections to the content, teaching abstract principles by establishing the need for them in a real-life context, and using analogies from students’ everyday lives, are practical methods to realize the underlying key feature of Thematic Integration. Connections to students’ everyday lives can be established in multiple places – within the lessons, through classroom and homework activities, by solving context-rich problems and while working on projects.

Collaborative learning

Collaborative learning (or cooperative learning, group work, team learning) is one method of getting students to actively participate in the process of learning. Several research studies show that students learn more of what is taught, retain knowledge longer, are able to solve more complex problems, and are more satisfied with the process when they learn in groups [Johnson and Johnson 1986, Toten et al 1991]. Students work on one or more tasks in small groups by planning, discussing and negotiating. Collaborative learning can take various forms: groups can be formal or informal, members can be assigned to groups by the teacher or students can self-organize, groups can last for a particular class or for a long-term duration (such as an entire semester, or for a project) and groups can be of varied sizes. Students co-construct and share knowledge, thereby forming a community of learners in the class.

Playfulness

Play is essential to development because it contributes to the cognitive, physical, social, and emotional well-being of children and youth. It allows children to use their creativity while developing their imagination, dexterity, physical, cognitive, and emotional strength. Research studies have revealed that play has been found to be the most developmentally appropriate way for children to learn since it facilitates problem-solving, perspective taking, social skills, and development of the mind (Bailey 2002). The role of play and the use of games as educational tools can influence learning among children by bringing about qualities such as confidence, self-efficacy, and intrinsic motivation (Garris et al 2002).
Hence it’s suggested including playfulness as an explicit basis for designing learning activities and transacting them in the classroom.

Computer curricula in Indian school Boards

Schools in India are affiliated to one of CBSE, ICSE, IB, IGCSE, or State Boards. Each Board
prescribes curricula and conducts standardized examinations for grades 10 and 12. A summary of computers curricula prescribed by these Boards is as follows:

• The CBSE Board follows the NCERT NCF 2005 [CBSE Board]. The NCERT (National Council of
Educational Research and Training) classifies computer literacy into six categories: Fundamental Operations and Concepts, Social and Ethical Issues, IT Tools, Communication Tools, Technology Research Tools and Problem Solving. The curriculum is categorized for three levels: Primary, Middle and Secondary schools. At each level, the categories are divided into competencies and skills to be developed. However these specifications are broad and there are variations in their interpretation across textbooks and schools.

• The ICSE Board has computers as a core subject in 1st to 8th grades, and as an elective in 9th to 12^th grades. The syllabi for 9th to 12th grades includes topics such as computer hardware functions, data representation and internal computer structure, computer software, social context of computing and ethical issues, algorithms, programming using a high level language and computers in everyday life. Details are available on their website [ICSE Board]. However the syllabi for the lower grades are left open. Schools are free to follow textbooks by any publisher that they find suitable. As a result there are variations in the topics covered, breadth of topics, concepts and skills taught at different schools.

• The IGCSE Board [IGCSE Board] based out of Cambridge and the IB Board [IB Board] based out of Geneva offers computer science and computer studies at various levels. However, there are not many schools in India that follow these curricula.

• Some State Boards in India have introduced computers as a subject, with varying degrees of syllabus specification. A pioneering effort is the IT@School project by the State govt. of Kerala which provides a comprehensive curriculum and teaching resources for various grades [IT@School project]. However for most other states the details of the topics to be covered and their depth are open to interpretation.

Computer curricula in other countries

There exist K-12 Computer Science curricula in many countries. Some examples are:

• The Association for Computing Machinery (ACM) Task Force Report [ACM K-12] provides a
curriculum and well-defined methodology to integrate teaching of computers and information technology into K-12 grades. Computer skills are learnt by carrying out projects and computer-based activities in other subjects.

• The International Society for Technology in Education (ISTE) [ISTE] defines standards for
evaluating skills and knowledge that students need to live productively in a digital world (NETS-S). The milestones describe what students should know and be able to do by the end of various grades, in technology operations, information fluency, problem-solving, creativity, collaboration, and ethics.

• The European Computer Driving License [ECDL] foundation offers international computer skills certification from introductory to advanced levels. The programmes contain modules which define the ‘skills and competencies to be a proficient user of a computer and computer applications’.

• Governments of several countries define their own curricula, learning objectives and competencies for CS education (also called Informatics, or IT) at the school level. [Hubwieser et al 2011] note that there is a variation not only in the content to be taught and at what level, but also in the levels of specificity described. They describe a research framework (called Darmstadt model), to systematize descriptions of school CS education across countries.

Integrated models such as the one from ACM are desirable but this approach is not suitable for Indian schools. Two key limiting factors are the lack of various resources and low computer skills among the teachers. Hence a comprehensive curriculum tailor-made for the Indian context is required.

Underlying Philosophy

This document addresses three purposes of a curriculum:

(i)                 Curriculum as a body of knowledge to be transmitted,

(ii)               Curriculum as an attempt to achieve certain ends in students, and

(iii)             Curriculum as a process.

The various choices made to address these purposes are influenced by the underlying philosophy, which is as follows:

1.      Develop computer fluency, not just computer literacy.

While computer literacy is defined as the knowledge and ability to use computers and related technology efficiently, computer fluency means a robust understanding of what is needed to use information technology effectively across a range of applications. The goal of computer fluency is to enable students to adapt to the changes in digital world rather than merely be aware about computer and its application.

2.      Develop thinking process skills, not just content mastery.

While content mastery (domain knowledge) is important, the need to develop thinking process skills (cognitive processes used by experts) is well established [Padilla 1990; Big6 skills]. Hence, curriculum should have explicit emphasis on teaching of thinking process skills, which are the basic procedures and methods used in making sense of complex situations, solving problems, conducting investigations
and communicating ideas. Computer literacy skills are introduced only after motivating the need for developing the corresponding thinking process skill.

3.      Highlight the interconnectedness of knowledge, not just address a topic/subject in isolation.

While mastery of a topic is important, recognizing the inter-connectedness of various topics and ideas leads students to construct a more expert-like knowledge structure [Ellis and Stuen 1998]. Hence, emphasis should be on:

(i)                 thematic integration, i.e., the integration of knowledge from various subjects into the Computers curriculum, and the use of computer-skills activities to strengthen knowledge in other subjects, and

(ii)               spiral curriculum, i.e., the content of the curriculum is organized such that themes and topics are revisited with increasing depth in each successive visit.

    Key Features

•      Thinking process skills
•     Computer literacy integrated with fundamental concepts and thinking skills
•     Thematic integration
•     Spiral curriculum
•    Scalability 

The philosophy led to the identification of key features. Now, we describes the process followed to operationalize the features into topics to be taught at each grade. As mentioned above, categorize topics into Concepts, Usage Skills and Social Aspects. The process used for coming up with the curriculum details is as follows:

1. Identify what concepts, usage skills and social aspects are relevant for K-12 levels, keeping in mind the key features of integrating computer literacy with thinking skills. This led to the identification of the following themes: Familiarity with computers, Computer applications, Thinking skills, Computer programming, and Social values.

2. Organize the themes into sub-themes and topics to be taught in each grade by applying the spiral design. The age-appropriateness of the topics is addressed by the spiral design.

3. Define learning objectives for the topics in each grade. The learning objectives are measurable indicators of the performance of a student in that topic [Anderson and Krathwohl 2001].

Integration of Technology into the Curriculum: An Interdisciplinary approach

Integrating technology into classroom instruction means more than teaching basic computer skills and software programs in a separate computer class. Effective tech integration must happen across the curriculum in ways that research shows deepen and enhance the learning process. In particular, it must support four key components of learning: active engagement, participation in groups, frequent interaction and feedback, and connection to real-world experts. Effective technology integration is achieved when the use of technology is routine and transparent and when technology supports curricular goals.

Many people believe that technology-enabled project learning is the ne plus ultra of classroom instruction. Learning through projects while equipped with technology tools allows students to be intellectually challenged while providing them with a realistic snapshot of what the modern office looks like. Through projects, students acquire and refine their analysis and problem-solving skills as they work individually and in teams to find, process, and synthesize information they've found online.

As with many teaching strategies, there are common methods in using technology that can be applied across various academic disciplines and grade levels. Having a set of generic models and strategies that are multipurpose in application assists teacher candidates in quickly developing technology-rich lessons for their fieldwork. This set can be continuously modified as experience in teaching increases through their student teaching.

To provide an overview of proven effective models and strategies, some are as follow:

Web-based lessons

§  WebQuests (http://edweb.sdsu.edu/webquest/webquest.html)

§      CyberGuides (http://www.sdcoe.k12.ca.us/score/cyberguide.html)

§      Filamentality (http://www.sdcoe.k12.ca.us/score/cyberguide.html)

Multimedia presentations

Telecomputing projects

Online discussions

Say if we take Webquest - A WebQuest is an inquiry-oriented activity in which most or all of the information used by learners is drawn from the Web. WebQuests are designed to use learners’ time well; to focus on using information rather than looking for it; and to support learners’ thinking at the levels of analysis, synthesis, and evaluation. Developed by Bernie Dodge with Tom March at San Diego State University, the WebQuest model has been effectively applied to all levels of education, from elementary to postgraduate study.

Example: The social studies curriculum for grades 6–8 contains investigations into relationships in our world. Topics include weather, life cycle, and communities in both science and social science. One WebQuest, hosted on the Pacific Bell Knowledge Network site, asks students to look at these relationships and aspects of life on our planet. The “Big Wide World WebQuest” (www.kn.pacbell.com/ wired/bww/index.html) uses a rubric appropriate for students at this age level. However, most students would not be ready to explore all of the activities; teacher may want to select a few activities that target their curriculum specifically. Some teachers in Grade 6 have chosen to include all the areas, reviewing foundation knowledge and adding more depth to student understanding of these relationships. As an example, one activity relating to language arts in the “Big Wide World WebQuest” asks students K–1 to link to International Symbols or hear animal sounds while looking at a picture of the animal. Students in third or fourth grade explore heroes of the world under the section entitled “People.”

The myriad resources of the online world also provide each classroom with more interesting, diverse, and current learning materials. The Web connects students to experts in the real world and provides numerous opportunities for expressing understanding through images, sound, and text.

New tech tools for visualizing and modelling, offer students ways to experiment and observe phenomenon and to view results in graphic ways that aid in understanding. And, as an added benefit, with technology tools and a project-learning approach, students are more likely to stay engaged and on task, reducing behavioural problems in the classroom.

SYLLABUS - CURRICULUM DETAILS

Themes and Topics

As indicated this section addresses the purpose of ‘curriculum as a body of knowledge to be transmitted’. The curriculum has been classified into five themes: familiarity with computers, computer applications, thinking process skills, computer programming, and social values and ethics.

Each of the themes has multiple sub-themes.

• Familiarity with computers: Topics in this theme provide opportunities to become familiar with computer associated vocabulary, learn computer and file operations, and acquire usage skills.
• Computer applications: Topics in this theme build competency in applications usage, such as word processor, presentation, multimedia, spreadsheet and Internet, thereby enabling students to utilize the potential of computer as users of the technology.
• Thinking process skills: Topics in this theme build cognitive abilities of algorithmic thinking, reasoning, problem solving, information gathering, brain storming and synthesizing, using multiple representations, and divergent thinking. These abilities enable students to plan and execute complex projects, use the appropriate applications for a given project, and write well engineered programs. In addition, these abilities equip students to deal with real life situations.
• Computer programming: Topics in this theme develop algorithmic thinking skills and enable students to become creators of technology. Computer programming is addressed in two phases, to avoid cognitive overload. A graphic user interface (GUI) based language to be used in the first phase, for learning of programming concepts. Text-based syntax is introduced only in the second phase, through a different language, such as Basic. The two phases are bridged by teaching how to draw flow charts and write pseudo-code.

• Social aspects – safety and ethics: Topics in this theme sensitize students to ergonomic, social and ethical issues associated with computer use. These issues are incorporated in the curriculum by way of exercises to avoid computer related injury, Internet safety guidelines, and values such as sensitivity to others and intellectual property rights.

The above themes are further detailed into sub-themes and topics at each grade level.

CONCLUSION

The model curriculum should develop computer fluency and thinking skills, in a manner that highlights the interconnectedness of knowledge. It uses a spiral curriculum design to ensure that students retain their learning and progress to deeper levels. The detailed specification of learning objectives for each topic at each grade may help to standardize the  competencies expected from students at each grade, and enable teachers to focus creativity on ‘how to teach’ rather than ‘what to teach’. Curriculum based on above suggestion can equip students with computer concepts, usage skills, and also the 4Cs of 21st century skills - critical thinking, communication, collaboration and creativity [Trilling and Fadel 2009].

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Education_Links.html>.

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An Adaptive Learning Structural design for Next Generation Simulation Learning Systems

An Adaptive Learning Structural design for

Next Generation Simulation Learning Systems

In recent years there has been an increased use of serious games or immersive learning simulations to measure high-level learning processes and accelerate the transition toward expertise by motivating learners to acquire knowledge and skills by presenting instruction in dynamic, entertaining, and creative ways. As serious games have evolved, so has their design to accommodate user needs and simulate real world experience through high-fidelity visuals and interactions (Zielke, et al., 2009). Although user needs and hi-end visuals are important to user experience during game play, game design should concentrate on providing a contextualized, adaptive learning experience with detailed feedback given to a player based on his performance level. To address this issue, we have designed a theoretical framework that focuses on providing an adaptive learning experience whereby a user can progress or regress to appropriate skill levels in the simulation based on his response or non-response to well-crafted stimuli. The model is based on research examining how learners acquire new skills and make decisions in their natural settings under high stakes, time pressured conditions. In addition, we have applied this model as an enhancement to an existing government– owned, web-based platform that supports and trains decision-making at both operational and tactical levels. In 2008, the use of serious games as an effective training tool for learning and skill development of today’s workforce was predicted to reach 1.5 billion dollars in global market sales (Derryberry, 2007). Serious games are considered different from traditional video games because their intended objective is to educate military and corporate organizations with measurable and sustained outcomes in order to improve performance and behavior instead of just for recreation or personal use (Zyda, 2005). In this paper, we will describe several types of adaptive learning environments and present a theoretical design framework that illustrates user progression in a multi-tiered scenario-driven simulation environment. Also, we will discuss the components that constitute scenario-driven adaptive training systems, describe how the use of dynamic pathing and active sequencing in simulation design can allow players to assess and reflect upon their initial knowledge and skill level prior to and after game play, and then examine the criteria for advancement of performance levels. Finally, we will review a conceptual design of an After-Action Review that can show traceability of user performance in an adaptive simulation system and provide remedial training recommendations to the learner.

ADAPTIVE LEARNING ENVIRONMENTS

The emergence of adaptive learning environments for web-based education has been in existence since the early days of the internet (Brusilovsky, 1999). According to Brusilovsky, Pesin, and Zyryanov, (1993), adaptive learning environments are intelligent educational systems that combine features of traditional Intelligent Tutoring Systems (ITS) with hypermedia components which adapt and record learner performance as players interact with the system. Over the years, these system environments have manifested into multiple categories or types.

Brusilvosky & Paylo, (2003) and Specht & Burgos (2006) categorized adaptive learning environments into seven areas:

· Interface-based: This environment focuses on the user interface elements such as color, size, and shadow to support adaptive learning.

· Learning-centered: This environment focuses on the learning process by dynamically adapting the content to the instructional sequence the content in various ways. The learning path changes every time the learner starts.

· Content-based: This environment focuses on the presentation of content as it adapts to the learner’s experience. A content-based interface may include adaptive navigational support to guide learners towards relevant and interesting information. For example, content-based adaptive learning environments may provide direct guidance, adaptive link sorting/hiding/annotating/generation.

· Problem solving support: This environment guides the user on the appropriate steps in order to solve problems. The guidance could come from an intelligent mentor programmed by a predefined set of rules.

· Adaptive information filtering: This environment focuses on providing information that is relevant and sequenced by the performance of the learner.

· Adaptive evaluation: This environment focuses on the system or assessment content changing based on the performance of the learner to simulated injects and/or guidance of an intelligent mentor.

· Adaptive timing: This environment focuses on the ability for a system to modify or adapt a path based on the learner’s performance within a designated time allotment.

Types of Adaptive Feedback

Within adaptive learning environments, simulation feedback plays a vital role in assisting learner performance. Traditional simulation feedback allows a learner to reflect upon his performance after game play in order to think through the decisions and problems made during the simulation. However, in an adaptive learning environment simulation feedback may or may not assist a learner after an event while still in game mode to solve problems and realize workable solutions. During and after game play, feedback may take on many roles to inform, correct, and disrupt learner performance. For example, a mentoring agent could provide critical facts about the situation in order to inform a player. However, if a player disregards or does not have time to read the information, he may not possess the data needed to make an informed decision, thus potentially resulting in a negative consequence. The second type of adaptive feedback is corrective. Corrective feedback presents information in order to help improve or re-adjust a player’s performance. For instance, if a player is continuously making bad decisions, a mentoring agent might take over and pause the game to have the player participate in a remediation assessment in order to teach the proper knowledge and skills needed to continue with game play.

Another example of corrective feedback could be a simulated inject designed to scold a player for not taking the proper action or inaction. The third and final type of adaptive feedback is disruptive. The purpose of disruptive feedback is to confuse, interrupt, or lure a player from taking action on a specific task or a set of tasks. For example, a player is tasked to write an email warning of a pending disaster to a specific simulated character. As soon as the player begins to write the email, he is disrupted by a telephone call, then an important email message, then a video, and so on. The disruptive feedback could be one or a series of lures to distract the player for accomplishing the task or objective.

ELEMENTS OF SCENARIO DRIVEN ADAPTIVE TRAINING SYTEMS

For the purposes of our adaptive framework discussed in this paper and the model of the technology platform used, there are several design elements which must be acted on in order to develop an instructionally sound adaptive learning experience. The narrative, timeline, and injects are critical design elements which drive immersive learning experiences. The first design element is the narrative. The narrative is the storyline which chronicles past and future events and provides context to the learner during game play. In order to fully engage learners, it is important that the narrative design account for immersion. For immersion to take place within a narrative, the words must express a captivating story with a dilemma or problem in which players must engage and make decisions in the situation. Additionally, the narrative should start off by presenting general information of an event and provide details about the environment. As the situation unfolds, information and events reveal greater information, which enables learners to construct meaning and begin to make sense of the story. Real-world situations place severe time-pressure on decision makers, and so should simulated events. Adding disruptions or information overflow can increase the feeling of time-pressure. However, if too much time pressure exists, learners may make only quick reactions that prevent them from assessing situations and thinking through responses. Another element used in our theoretical adaptive framework is the development of multiple timelines along which a learner can progress through the game. Timelines provide an instructional designer with a structure around which he can organize detailed simulated injects. Every major event poses an opportunity for learners to encounter new challenges in which they must make decision(s) and take action(s) which will affect exercise outcomes. The third and final design element to make up a scenario-driven adaptive training system are simulated injects. Injects are the driving components of serious gaming simulations, allowing learners to take action and perform tasks. Once an instructional designer establishes the narrative and timelines, he begins to create injects which adhere to the narrative and timeline. Several elements are important to consider when developing injects for adaptive serious gaming environments: Ø Content: body of information conveyed to the learner Ø

Type: inject form (phone call, live conversation, video, 3D interaction, etc.) Ø

Time: inject occurrence on the timeline Ø

Simulated Entities: characters to and from whom the information is conveyed

Feedback: standardized responses to the injects/stimuli Ø Consequence: positive and negative outcomes of responding to an inject

 Advancement Criteria: measures used to indicate whether or not a learner progresses to higher level challenges. Criteria may take the form of a correct or incorrect response, time used to take action or inaction, etc.

Realistic, well designed injects motivate learners to engage in game play to make decisions and take actions. For instance, if the learner is presented with a live conversation inject and dialogue content is too ambiguous or does not use proper domain verbiage, the learner may or may not respond to the stimulus, thus compromising its original intent. Associating negative or positive consequences to simulated injects is also important. For example, in our adaptive learning model if the learner does not perform or respond to a task and there are no repercussions (e.g. make a follow-up telephone call) then the learner will fail to recognize the purpose of the task, may or may not be demoted to lower performance level, and will not complete the overall task objective. Injects, along with their associated actions, should allow learners to gradually gain insight into the nature of the scenario (Davis & Kahn, 2007). Injects should provide learners with the opportunity to expand their experience base and ability to structure information as it is collected. In addition, well developed injects allow learners to focus and comprehend the situation and enable them to assess events and reflect on actions.

A CONCEPTUAL MODEL OF AN INTEGRATED ADAPTIVE LEARNING ENVIRONMENT

The Importance Pre and Post-Testing

Pre- and post-testing can provide a measurement device for learners to assess their initial knowledge and skill levels in a particular domain or subject area and acts as a baseline assessment for them to select their appropriate skill level prior to game play. Pre and post assessments help an individual to practice the mission and think through potential problems and possible solution strategies. Additionally, preassessments can help activate already learned knowledge causing the player to have a potential advantage during game play because his mind is focused and primed on the tasks awaiting them. Post assessments help learners retain the knowledge and skills learned during the game by providing an opportunity for rehearsal. The more learners rehearse and practice with the appropriate instructional technique, the greater the likelihood they will be able to transfer the knowledge and skills into long-term memory (Clark, 2008).

Dynamic Pathing/ Active Sequencing

Dynamic pathing is the concept of taking different paths through a simulation based on the decisions made and actions taken within a defined time frame or what we call a “time horizon”. The decisions and actions selected by the learner are evaluated by the simulation portal in order to provide a customized learning experience tailored to his performance levels and abilities. Prior to game play the user selects an initial skill level or entry point into the simulation and then proceeds to play the immersive learning simulation (see Figure 1).

At the end of the first time horizon or timeline segment, the system analyses user performance based on the specific actions taken and decisions made in order to determine if the user should remain on the current timeline or be shifted to a alternate timeline based on his performance. In this way, the user’s experience is dynamically customized to provide an appropriate amount of challenge while playing the simulation. Figure 2 depicts a user who began playing the simulation on the “Novice” timeline and was shifted up to the “Intermediate” timeline at the end of “Time Horizon 1” based on good decisions and actions to simulation injects/stimuli that were presented within the timeline segment. Later in the simulation, difficulty levels for the learner were then subsequently increased further to the “Advanced” timeline and then back down to the “Intermediate” timeline at time horizons 2 and 3 respectively. This path through the simulation depicts a user who performed well and was promoted to more challenging timelines within the simulation. However, after reaching the “Advanced” timeline, the learner’s performance began to degrade during time horizon 3 and he was moved back down to the “Intermediate” timeline for the duration of the simulation (see Figure 2).

The concept of dynamic pathing can deliver many potential user experiences depending on what skill level is initially selected and what timeline paths the user follows through the simulation based on user performance. The notion of Active Sequencing provides for further customization of the learning experience within a timeline segment based on user performance. Based on the accuracy of decisions and/or actions made by the user, certain injects may be triggered or suppressed from being spawned within a time horizon which dynamically changing the user’s simulation experience. This feature helps the learner experience the consequences of his actions and decisions. By making good decisions, the learner can stave off potentially bad things from happening within the scenario. Conversely, making poor decisions or failing to take action can cause bad things to happen within the simulation similar to what happens in real life. Theoretical Design Approach Our theoretical adaptive framework is based on a model of performance and skill acquisition developed by Dreyfus and Dreyfus (1986). Their model describes a five-stage approach for skill and performance development ranging from novice to expert. Currently, the government-owned simulation platform used in conjunction with this conceptual model delivers game play at three varying levels of difficulty ranging from novice, intermediate, and advanced. These levels are selected by the learner at the beginning of the simulation.

Our enhancement to the existing serious gaming platform is to continue to give learners the option to select their initial competency levels, while allowing the simulation to adjust the difficulty level as the game progresses based upon the performance of its players. There are many games which currently offer their players a variety of novice, intermediate, and advanced modes of play.

Some, like Tetris, require an advancing player to perform essentially the same function at each stage, simply placing ever greater constraints on the time allotted to making decisions. Others, such as most racing games, present players with increasingly skilled opponents and require them to refine the subtleties of their own performance in order to achieve their objectives, while gradually limiting the margin for error. Games of this sort continually adapt in order to keep a player challenged, and can be highly effective for training a person to carry out specific tasks. Games in this vain are not, however, very useful instructional tools for teaching people how to effectively acquire and act upon information gathered from a variety of sources. To this point, few recreational nor serious games have yet been presented with environments which adapt to the ability of a player to manage dynamic and changing situations requiring more than the fulfilment of a single task.

A serious game which teaches its players to manage complex situations cannot adapt itself simply in speed of decision making or by limiting the margin for error. On the contrary, we propose that an effective training tool would in fact increase the possible margin for error by a rather large extent. The fundamental suggestion we are putting forth is that an integrated adaptive learning environment of this type is most effective when it offers its players an increasing level of freedom in choosing which actions to take and when to take them in response to the stimuli presented. Imagine a game in which a player has an ultimate objective at the end of a narrative, with a number of minor objectives set up along the timeline between the start and the finish, the resolution of which all have an effect on the success of the ultimate objective, but none of which can be singularly responsible for its success or failure. A novice player would be prompted by simulated entities with specific information and a choice of several pre-determined actions possible in response at set points within the timeline. He does not have a choice in when he receives the information, its source, or when to take action. His only freedom is to choose between several possible actions.

This format is actually employed already by a large number of games in order to familiarize the player with the interface. The idea to constrain the novice player’s freedom to make decisions is based on his limited experience and “context-free” rules in situations characteristic of their domain (Dreyfus and Dreyfus, 1986). Once the player has gained enough familiarity with the interface to know where information can be gathered and what sorts of actions are available within the simulated environment, however, this sort of guidance or mentoring should no longer be needed. At this point, a player reaches an intermediate stage. Obviously there can be several different levels of intermediate skill which a game can address. It is not important how many intermediate levels are available. The significant distinction between a novice and an intermediate player in the type of serious game we envision, however, is the freedom afforded the intermediate player in seeking information and choosing to act upon it.

 An intermediate player could be prompted with information by a simulated entity, for example, but not given any list of possible actions to take. He would have to decide upon his own action within the constraints of the simulated environment.

At another point within the narrative, a player could be presented with a minor objective, and a specific set of actions which could resolve the matter, but no information regarding which option would be most appropriate. It would fall upon the player himself to determine which of the different simulated entities within the game would provide the most useful information for achieving the objective. He could also be prompted with all of the information necessary to take a specific action, but given freedom to implement the action at a time of his own choosing, considering such variables as the changing resources available to him. Essentially the intermediate player is given a less rigid framework for achieving an objective than a novice player, but does not have to be completely self-reliant.

Also, he can choose where to find information, or what action to take, or when to take it, but not all at the same time. Because experts seem to have a highly tuned intuition that enables them to perceive situations and respond quickly and accurately (Klein, 1998), the advanced player, on the other hand, would be given wide freedom of choice in all of these matters. When an objective is presented, the player is responsible for consulting the appropriate simulated entities on his own in order to find out everything he needs to know in order to be able to choose a suitable action to take at an appropriate time. As much freedom as possible will be given to the player in order to accomplish each objective based on a variety of ways and varying degrees of success.

The potential for advancement between the levels will be determined by an assessment of each minor objective within the timeline. A novice should be advanced to the (first) intermediate level simply by completing his first objective. Effort should be made by the creators of the game to provide the player with as much exposure to the interface as possible within the framework of the first objective in order to assure a smooth transition. At the intermediate level, however, advancement should be granted only for a high degree of success in accomplishing a specific objective. This success can be measured in a variety of ways. A player who achieves a lower degree of success in completing an objective should be dropped down a level, where the increased level of prompting by simulated entities and constraint in available actions should help him focus more clearly upon his specific objective.

Furthermore, we suggest that a player be given the option to switch between his current level and novice level at any point, in case he needs the mentoring or interface clarification supplied there. Assessment of a player’s performance at the intermediate and advanced stages requires first that an objective be broken down into constituent components, such as information gathering, type of action, time of action, etc. If, for example, the game prompts the player with an objective, and the designers of the game have written the narrative such that there are four pieces of information held by the simulated entities which would be useful to the player in making a decision about how to act, a player would ideally take an action immediately after receiving the fourth piece of information. Few players could be expected to act so precisely, however. If information gathering were plotted on a bell curve, with four pieces of information at the apex, then a player who took action after receiving the fourth piece would be awarded a maximum score.

 If he acts too soon, with only three pieces of information, his score will be slightly less, but not significantly so, and when the objective is completed, the game will prompt him with feedback including the piece of information which was missed and how it applied to the decision to act. If the player continues to seek information after receiving the fourth piece, perhaps not realizing that he already possesses all of the knowledge needed to take responsible action, the assessment will account for each additional attempt to acquire information from simulated entities.

Prompting one or two entities for information will only have a slight effect on his overall score, but continued inquiry will have increasingly negative effects as the slope of the bell curve becomes steeper. Similarly, if he acts before acquiring much information at all, his score will be more highly impacted than if he had missed only one relevant piece of information. It is a simple matter to include in the assessment of each objective a clear explanation of why each of these pieces of information is important within the context of the objective.

 If the variable is time, an in-game clock could be started at a specific point along a timeline. The player is expected to take an action at a time of his choosing between the start and the stop of the clock. An ideal time for action must be chosen by the game designers. A bell curve could be drawn over that period of time. If the player acts too soon, or too late past the ideal time for action, he would receive a much lower score than if he acted within a standard deviation of the ideal moment. When the objective is completed, a less successful player could be prompted with specific reasons as to why he should have acted sooner or later than he chose to act, and how that choice affected the resolution of the objective.

If we imagine a situation which combined variables in both time and information gathering, it is possible that the player finds himself unable to acquire all of the relevant information by the time the ideal moment for action in the timeline arrives. If he takes action at this point, he should be given a full score for the time of the action, and a reduced score for the amount of information he had when he acted. The prompt after the resolution of the objective should explain to him that the time to act was appropriate, but reveal to him the significance of the information which he failed to acquire, and advise him where to locate similar pieces of information when encountered with future objectives in the same vain. The more advanced a player is, the more variables an adaptive learning simulation would present him with.

Figure 3 details a situation where a player has the freedom to choose between a number of possible actions, and to decide for himself the best time to take those actions. The combination of the three graphs shows how the bell-curve assessment strategy may be applied to similar situations, where freedom is afforded to a player within multiple variables in a simulation. The action assessment graph, on the left, is tilted ninety degrees from customary orientation for convenience. In this simulation, there are seven actions labelled A through G that are available to a player. Action D is theoretically the best solution to the scenario presented, and a player who chooses action D would receive the highest possible score from this graph for that choice. The time assessment graph shows that the best time for a player to take an action in order to resolve this scenario is at time signature 3.

Acting within a standard deviation of time signature 3 still has a profoundly positive effect on the resolution, but the further from time signature 3 that a player takes action along this timeline, the less effective his action will be in resolving the situation. Nevertheless, taking any sort of action in order to resolve the situation, even if grossly late, still has some value. It is for this reason that the bell curve is particularly suitable to these assessments, rather than a straight line. The graph showing the availability of actions over time, however, complicates the matter. Rarely, in a real world situation, are all actions available to a person at all times. Actions A and F, for example, are available essentially for the duration of the simulation. Action E, however, is available only at the beginning and end, and action D only after about time signature 4.8. As the simulation plays out, the actions available to a player at any particular moment can change. Theoretically, the best action to take and the best time to take it would be action D at time signature 3. This theoretical maximum is represented by the red dot. As one can see, in this particular simulation, a player does not have action D available at time signature 3, and is therefore forced to make a choice about taking less than-ideal actions at less-than-ideal times. The blue dot represents a relatively successful choice by a player, who takes a very good action, even if slightly early. The green dot represents a player who takes the exact same action, but far too late for it to resolve the scenario in an effective manner. The numbers next to each dot are the sum of the assessed actions and time signatures from their respective graphs. The assessment numbers in this specific graph, however, are quite arbitrary, and can be adjusted to fit any specific simulation.

Here, they are merely intended to illustrate a relative difference between possible choices. As one can see, the freedom afforded to an advanced player in such an environment greatly increases the margin for error from an ideal. For that reason, it is important that the feedback which a game provides to a player after the completion of an objective take these matters into consideration. The player represented by the blue dot should be praised for choosing a suitable action, even if it is not the ideal solution to the situation, because he acted in a timely manner. The player represented by the green dot, on the other hand, should not only be corrected for delaying his action for such a long time, but also for choosing a less-than-ideal action when the ideal action was available to him. A less advanced player presented with the exact same scenario would be limited with respect to one of the variables. He could, for example, be prompted by the game and told that he must take action E. He would then have the freedom to choose when to take that action, but nothing else. Conversely, a less advanced player could be prompted to take action at time signature 4. He would have the free choice between the five possible actions available at that time, but nothing else. A more advanced player, on the other hand, would be presented with the freedom of choice in increasingly greater numbers of variables, such as the gathering of information or the tapping of resources. No matter how many variables are included, however, assigning specific values to the choices available to a player, as we do here, makes it a simple task for the designer of a game to set limits above and below which the level of a game will automatically change. Perhaps our player represented by the blue dot will advance to the next level of difficulty because he scored above a 75, and our player represented by the green dot will regress for scoring below 55. The specific numbers are unimportant, and depend upon the discretion of the game developer. Bell curve assessments, however, are a simple way of quantifying the results of decisions made by players with respect to multiple variables.

CONCLUSION

The purpose of our theoretical adaptive framework discussed in this article is to demonstrate a blueprint toward developing an adaptive serious gaming system that could provide a greater opportunity for an organic learning experience whereby individuals can be consistently challenged in a meaningful way and granted freedoms to face challenges as they arise. This framework is meant to be a starting point for modelling, simulation, and educational professionals to continuously refine and advance as adaptive learning technologies are developed and implemented.