Intelligent Tutoring Systems by and for the Developing World: A Review of Trends and Approaches for Educational Technology in a Global Context <s> Cultural and Language Localization <s> The Tactical Language and Culture Training System (TLCTS) helps learners acquire basic communicative skills in foreign languages and cultures. Learners acquire communication skills through a combination of interactive lessons and serious games. Artificial intelligence plays multiple roles in this learning environment: to process the learner's speech, to interpret and evaluate learner actions, to control the response of non-player characters, to generate hints, and to assess the trainee's mastery of the skills. AI is also used in the authoring process to assist in the generation and validation of lesson content. This article gives an overview of the system, and describes the experience to date in transitioning the system from research prototype into a training system that is in regular use by tens of thousands of users in the United States and elsewhere. Experimental results from field studies are presented, relating learning outcomes, motivational effects, and the role of game-based learning and intelligent tutoring in achieving the learning outcomes. <s> BIB001 </s> Intelligent Tutoring Systems by and for the Developing World: A Review of Trends and Approaches for Educational Technology in a Global Context <s> Cultural and Language Localization <s> Language learning resources are constantly evolving alongside technology. One of such resources is REAP.PT, a system which aims to raise users proficiency in the Portuguese language in an interactive manner. Its current features include text-based exercises. This paper describes the evolution of REAP.PT aiming on locative prepositions used to describe the spatial position between objects. In this new REAP.PT, exercises take place in a 3D environment, and are complemented with gaming aspects to make them more appealing to students. The game scenario is an office, where each room contains different exercises. Completing exercises awards the student with points that unlock harder rooms. This provides the student with a challenge and a sense of progression. We believe that with these gaming aspects, students will have increased motivation to complete exercises. <s> BIB002 </s> Intelligent Tutoring Systems by and for the Developing World: A Review of Trends and Approaches for Educational Technology in a Global Context <s> Cultural and Language Localization <s> Technology has the promise to transform educational prac-tices worldwide. In particular, cognitive tutoring systems are an example of educational technology that has been ex-tremely effective at improving mathematics learning over traditional classroom instruction. However, studies on the effectiveness of tutor software have been conducted mainly in the United States, Canada, and Western Europe, and little is known about how these systems might be used in other contexts with differing classroom practices and values. To understand this question, we studied the usage of mathematics tutoring software for middle school at sites in three Latin American countries: Brazil, Mexico, and Costa Rica. While cognitive tutors were designed for individual use, we found that students in these classrooms worked collaboratively, engaging in interdependently paced work and conducting work away from their own computer. In this paper we present design recommendations for how cognitive tutors might be incorporated into different classroom practices, and better adapted for student needs in these environments. <s> BIB003
Culture and language are combined because the literature seldom addresses culture without addressing language. The most endemic examples of localization occur between or within most-developed countries, such as switching between US and UK English or supporting multicultural regions and institutions. Localization expands beyond language to icons, graphics, and mother media. Localization and supporting users with different native languages have been addressed by a few established ITS architectures. All of these ITS were localized manually. Cognitive Tutor was localized into Spanish and Portuguese by working with local teachers to revise each problem BIB003 . REAP (REAder-specific Practice) was extended from English to Portuguese by researchers who created an equivalent vocabulary list and extended the ITS BIB002 . TLCTS (Tactical Language and Culture Training System) worked on the opposite issue: localizing training scenarios to support US soldiers' learning of different cultures BIB001 . These accounts all involve skilled local or expert involvement in the project. It is unclear if more efficient alternative practices are possible. Design patterns that separate graphics and text as replaceable assets can ease this process. For example, graphics should not include text because a duplicate graphic would be needed for each language. Web applications and learning management systems standards (e.g., SCORM; scorm.com) support multiple languages by adding markup that designates the language and dialect using International Organization for Standardization (ISO) standards (ISO-639; www.iso.org/iso/home/standards/language codes. htm). Open standards such as gettext have also been designed for cross-language code development and applications (www.gnu.org/software/gettext/). However, content extends beyond basic translation and graphics. Local knowledge and cultural understanding are key barriers. Crowd-sourcing services have been used to tag other ITS content, but these techniques have not been explored for ITS localization  . Services such as Amazon's Mechanical Turk (www.mturk.com/mturk) could provide a low-cost solution to localize content or verify that content has been localized effectively. However, if low cost leads to low quality, crowd sourcing will be ineffective. Research is needed to determine how crowd-sourcing could support high-quality localization, such as localization tasks, processes to monitor reliability (e.g., multiple raters), and boundary conditions (e.g., which content needs expert input). A final model for localizing an ITS is to localize only the authoring tools, documentation, and certain code functionality (e.g., character sets), rather than any of the content. This approach has been used successfully by the open-source KDE operating system environment (www.kde.org), which is available in over 100 languages. In the ITS community, AutoTutor Lite  ) has a Chinese-language prototype that is under development. This version uses authoring tools and documentation translated into Chinese, and Chinese natural language processing functionality is being refined. Compared to content, authoring tools require less localization effort. However, this approach requires local educators or researchers to generate their own tutoring content. This has two major pitfalls. First, tutoring content must be almost completely redeveloped. Since content is not reused, this shifts labor and time costs to local developers. As such, localization effort is shifted from paid experts adapting content to independent authors creating their own ITS content. Second, if local stakeholders struggle to create effective content, it may reflect badly on the tutoring system. Significant training might be required to help local developers author effectively. However, this loss of control is also an advantage. Local developers and authors gain the ability to develop and prototype ITS lessons based on their own goals. Given the freedom to develop their own ITS content, local stakeholders can address topics that developers from most-developed countries did not consider or were uninterested in designing.