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Research: Adaptive Serious Games For Learning


Via: Gaming Lab

Gaming Lab Blog has recently posted Scenario Adaptivity in Serious Games that provides some food for thought when building "Serious Games" context for learning.

The author is a PhD student in Game Technology at TU Delft University, in the Netherlands. He is working on semantic modelling and adaptive gameplay in the Computer Graphics and CAD group.

According to the author, “Serious Games are becoming increasingly established, but they are still coming of age in terms of player experience. Most Serious Games are developed ad-hoc and lack sound theoretical foundations, which leads to a number of drawbacks: they are predictable, impersonal and limited by stereotyped training scenarios. In particular, Serious Games should be designed to prevent (i) training modules from following rigid patterns, (ii) unattractive and predictable game-play, (iii) little advantage being taken of user data collected throughout the game and, worst of all, (iv) little knowledge being employed to guide the course of the game. For example, it would not be effective if all medical trainees in a certain course would have to follow the same timed procedures, in the same standard scenarios, independently of their personal skills or difficulties; and it would be (pedagogically) even worse if their final scores could not be traced back to particular in-game moments. Trainees might just learn how to play the game, instead of how to think and act in similar scenarios.”

The author adds:

“Many researchers agree that "Serious Games" have to become more challenging, unpredictable and user-centric, to be fully embraced as an effective way of knowledge transfer. To prevent the shortcomings above, Serious Games should include virtual scenarios that adapt to what and how players need to learn in a given context. This scenario adaptivity should benefit players, by providing them with more flexible challenges and a broader range of (pedagogically) meaningful ways to solve them.”

With his research, the author expects to contribute with a methodology for supporting the creation of such adaptive virtual scenarios. This methodology should focus on adapting scenarios to: what players need to learn, how they should learn it and what did they failed to learn.”

The argument is that instructors already possess this specific knowledge and, as so, are in a privileged position to steer scenario adaptivity to the expected benefits. The Instructor would use his knowledge on what should be learned by a specific player, to automatically generate virtual scenarios that are suited to player characteristics and learning goals. The Instructor would create in-game situations where objects and events adjust, in real-time, to players’ performance and the way they should be learning.

The author’s main goal is to embed such knowledge into game worlds and objects, which will become more meaningful in different ways of adapting to benefit players.

Research on Adaptive Games, Adaptive Game-Based Learning and Adaptation Engines

Via: Gaming Lab

According to Gaming Lab, Adaptive Games are a growing research interest. The thesis is that an intelligent game that is able to adapt itself to the characteristics of an individual player will provide a much better gaming experience and ultimately attract a wider audience.

At the same time Prof. Dr. Helmut Schauer, from Universität Zürich, Wirtschaftswissenschaftliche Fakultät, Informatik, Institut für, states that “Adaptive Game-Based Learning is a fundamental issue for the next generation of educational games where progress is controlled in accordance to the learners’ behavior.”

“The major aim for an adaptive game-based learning system is to support and encourage the learner considering his needs, strengths and weaknesses”, he says. “This new kind of educational game rather becomes a personal trainer than a training machine. Not only the degree of difficulty of the tasks is adjusted to the learners’ ability level, but also the system reacts to personal learning styles and preferences.

This research seeks to assess the impact of adaptivity for the learning outcome of an educational serious game. The goal is to create a generic control module that “calibrates” the adaptation between the educational game and the player.

Relevant parameters shall be determined experimentally in a prototype of a learning game. The crucial question of how to measure learning success still has to be investigated. The results will be classified and should indicate specific learning types for educational games.

(The results of this thesis should lead to guidelines for the design of adaptive learning games - Weitere Informationen).

Another research, Adaptive Serious Games Using Agent Organizations, from Universiteit Utrecht, states that increasing complexity in Serious Games and the need to reuse and adapt games to different purposes and different user needs, requires distributed development approaches.


“The use of software agents has been advocated as a means to deal with the complexity of Serious Games”, say the authors. “Current approaches to dynamic adjustability in games make it possible for different elements to adjust to the player. However, these approaches most use centralized control, which becomes impractical if the complexity and the number of adaptable elements increase. The Serious Games we are investigating are developed using complex and independent subtasks that influence each other. In this paper, the authors propose a model for game adaptation that is driven by the player, the game objectives and the agents. In particular they focus on how the adaptation engine determines tasks to be adapted and how agents respond to such requests and modify their plans accordingly.

“The use of software agents has been advocated as a means to deal with the complexity of Serious Games”, say the authors. “Current approaches to dynamic adjustability in games make it possible for different elements to adjust to the player. However, these approaches most use centralized control, which becomes impractical if the complexity and the number of adaptable elements increase. The Serious Games we are investigating are developed using complex and independent subtasks that influence each other. In this paper, the authors propose a model for game adaptation that is driven by the player, the game objectives and the agents. In particular they focus on how the adaptation engine determines tasks to be adapted and how agents respond to such requests and modify their plans accordingly.

The Press On Adaptive Games Promise High Scores For Everyone

Via: New Scientist

Extracts

Computer games have had an element of adaptability for decades, says Julian Togelius at the IT University of Copenhagen, Denmark. "If you play well the game gets harder and if you are lousy it might get easier," he says.

Togelius and colleague Georgios Yannakakis want to take this adaptability one step further by creating games that "learn" to identify whether an individual is a fun-junkie or a challenge-seeker, and then tailor later sections to suit these tastes. Two people might ultimately play very different versions of the game - but both should be satisfied by the experience.

To investigate the idea, the researchers altered the game Super Mario Bros, varying parameters such as the number and type of enemies and the size of gaps between platforms in response to how the players fared. The game also records a player's moves, including how often they run and jump, and the time spent standing still.

Volunteers then played two slightly different versions of the game and were quizzed about which version they found more challenging or predictable, fun or frustrating. The researchers used algorithms to identify which particular suite of parameters is associated with different gaming experiences.

Some early results appear obvious. "If you die by falling too often down gaps that is indicative of frustration," says Yannakakis. However, the approach goes beyond "common sense" associations to uncover those that are not so readily apparent, he says. In Super Mario Bros, for example, hitting bricks to release coins or stomping turtle shells and throwing them - activities not necessary to accomplish the overall goal - positively correlate with a fun experience, Togelius says.

While some games developers are interested, "there is also considerable resistance to these ideas", says Ian Bogost at the Georgia Institute of Technology in Atlanta. "Some wonder if this effort destroys the potential for art to produce the unfamiliar or disturbing."