"1. Introduction. According to George Siemens, learning analytics “is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning” (http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics). The LAK 2011 conference call for papers defines learning analytics as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.” In this paper, we present our vision of leveraging learning analytics tools and techniques to support teachers‟ dynamic diagnostic pedagogical decision-making in actual K-12 classroom settings. Our vision seeks to extend the current state-of-the-art in learning analytics in at least four directions, to apply learning analytics in the primary and secondary education formal classroom settings compared to tertiary education settings, focus on real-time use of learning analytics by teachers for technology enhanced formative assessment, apply an extended version of the pair analytics method in visual analytics, and finally, to review and build on current work in the learning sciences and the method of design-based research. The primary contribution of our paper is the presentation of the preliminary triadic model of teaching analytics (TMTA). The remainder of this paper is organized as follows. Section 2 presents prior empirical work documenting cultural influences in online learning settings. Section 3 first presents cultural differences in teaching and learning in formal classroom settings, communication styles and cognitive processes and then discusses the implications for online learning and learning analytics. Section 4 concludes the paper with the identification of several challenges and directions for future work. 2. Related Work. We present below a selective survey of prior empirical work that documents crosscultural differences in online learning. Vatrapu [1] found that despite differences between American and Chinese cultural group participants on (a) how they used the tools and resources of the learning environment (appropriation of affordances) and (b) how they related to each other during and after their collaborative learning interactions (technological Intersubjectivity), there were no significant individual learning outcomes differences. Kim and Bonk [2] report cross-cultural differences in online collaborative behaviors of the US, Finnish and Korean participants in their study. Daniels, Berglund and Petre [3] found cultural differences in international projects in undergraduate CS education. McLoughlin [4] based on her experiences with developing web-based instruction for Australian Indigenous education calls for a culturally responsive technology. Iivonen, Sonnenwald, Parma, and Poole-Kober [5] found culturally influenced differences in language and communication styles in a library and information studies course taught over the Internet in Finland and US. Walton and Vukovic„s [6] work with south African students from disadvantaged backgrounds found that cultural differences make it difficult for the students to make the transition to the web use. Crump [7] explored the effects of computing learning environment on the newly arriving international students at universities in New Zealand. The author reports that the cooperative and collaborative learning environment was an issue of concern to the students. The author says it is likely due to the oversimplification of social structure of groups, individual and group goals and the diverse nature of knowledge construction in the collaborative learning environments. Duncker [8] conducted an ethnography of the usability of a library metaphor used in digital libraries in the cultural context of the Maori who are the indigenous population of New Zealand. Duncker says that metaphors and metaphorical thinking are strongly rooted in culture. The Maori found the digital libraries interesting but difficult to use due to the breakdown of the library metaphor caused by a number of cultural misfits. Keller, Pérez-Quiñones and Vatrapu [9] outlined cultural issues and opportunities in computer science education. In the next three sub-sections, three separate lines of empirical findings from the fields of social behavior, communication and cognition are presented and implications for online learning are discussed. 3. Culture and Behavior. Cultural models can be used to identify the differences in cultures that affect the computer supported collaborative learning environments. There are two kinds of cultural models: models that use typologies and models that use dimensions. Typologies describe a number of ideal types each easy to imagine. Dimensional models group together a number of phenomena in a society that were empirically found to occur in combination into dimensions. Typologies are difficult to adopt in empirical research as real cases very rarely correspond to one single ideal type. 3.1 Hofstede’s Cultural Dimensions Model. Hofstede‟s seminal work on cultures in organizations formulated a framework of four dimensions of culture identified across nations. Each dimension groups together phenomena in a society that were empirically found to occur in combination. In this section, Hofstede‟s definitions for these original four cultural dimensions are listed followed by a discussion of each dimension with respect to online learning. Hofstede‟s cultural dimensions model indicates what reactions are likely and understandable given one‟s cultural background. 3.1.1 Low Power Distance vs. High Power Distance. Power distance is the “extent to which the less powerful members of institutions and organizations within a country expect and accept the power that is distributed unequally” [10, p.28]. People in large power distance cultures are much more comfortable with a larger power/status differential than small power distance cultures. Table 2.1, adapted from Hofstede [11, p. 313], outlines the effects of power dimension that have implications for online learning environments. It is important to note that Hofstede‟s conception of power distance is not a bi-directional one; it is conceived as a subordinate‟s expectation and acceptance of unequal distributions of power in a social setting. Table 3.1: Power distance dimension in traditional classrooms. If online education is offered as an alternative to traditional schooling then it is important to investigate how students perceive the social affordances of the virtual learning institutions. In the context of collaborative problem solving, students coconstructing concept maps are provided information attributed to scientists who have authority by virtue of their expertise and experience. Arguments from authority are valued in the scientific enterprise if those authorities themselves adhere to the scientific method. The point here is not whether the issues of power distance will show up in online classrooms but rather how does this dimension help understand the interactional behavior in an online learning setting. Power distance becomes an important dimension to consider in collaborative problem solving involving students from lower and higher ends of the relatively ordered dimensional scale. Collaborative learning does away with the traditional instructional role of a teacher. Collaborative learning replaces the teacher-student dyad with a student-student dyad, replacing a didactic pedagogical approach with a social constructivist one. In the case of high power distance cultures, this reconfiguration in learning results in a replacement of the more hierarchical power structures with flatter ones. Do students take advantage of this in an online learning setting? From a cognitive standpoint, it is interesting to investigate how “cultural schemas” adapt in this reconfigured learning setting. For example, what would be the role of confirmation bias in problem solving in intercultural collaborative learning environments? Do students from high power distance cultures conform to the expert opinion even in cases where it explicitly contradicts the available evidence? What role does the collaborative other play in these learning interactions? These are a few of the questions that become relevant when the power distance dimension is considered in intercultural online learning settings. 3.1.2 Individualism vs. Collectivism. “Individualism pertains to societies in which the ties between individuals are loose: every one is expected to look after himself or herself and his or her immediate family. Collectivism as its opposite pertains to societies in which people from birth onwards are integrated into strong, cohesive in-groups, which throughout people’s lifetime continue to protect them in exchange for unquestioning loyalty” [10, p.51]. This dimension describes the degree to which a culture emphasizes an individual‟s reliance on the self or the group. Table 2.2, adapted from Hofstede [11, p. 312], outlines the effects this dimension that have implications to online environments. This dimension is of particular interest to the social constructivist theories of learning given the small group size emphasis. In inter-cultural online learning groups, dynamics of in-group and out-group memberships might affect how certain technology affordances are appropriated as social affordances. They might also affect the perception of other students in the online learning environment. The notion of face-saving is of important when it comes to subjective perceptions and evaluation of the user interface, online interaction and instructional elements of an online course. Table 3.2: Collectivism vs. individualism dimension in traditional classrooms Based on socio–cognitive conflict theory [12], collaborative learning effectiveness is thought to be influenced by the extent that students jointly identify and discuss conflicts in their knowledge beliefs [13]. This works well in an individualist culture but in collectivist cultures consensual forms of intersubjective meaning making processes may be more prevalent. 3.1.3 Femininity vs. Masculinity. “Masculinity pertains to societies in which the gender roles are clearly distinct; femininity pertains to societies in which the gender roles overlap” [10, p. 82]. This dimension refers to expected gender based division of labor in a culture. The cultures that score towards what Hofstede refers to, in a confusing choice of category labels, as ""masculine"" tend to have very distinct expectations of male and female roles in society. The more ""feminine"" cultures have a greater ambiguity in what is expected of each gender. Table 2.3, adapted from Hofstede [11, p. 315], summarizes the implications of this dimension for online learning environments. Table 3.2: Femininity vs. masculinity dimension in traditional classrooms Collaborative learning is often distinguished from cooperative learning by the argument that collaboration involves joint activity or an effort to maintain a joint conception [14] whereas cooperation involves a mere joining of individual activities [15]. Collaboration is often conceived of as being beyond a basic division of labor and more of an enterprise involving parties with equal stakes. 3.1.4 High Uncertainty Avoidance vs. Low Uncertainty Avoidance. “The extent to which the members of the culture feel threatened by uncertain or unknown situations”[10, p. 113]. This dimension refers to how comfortable people feel towards ambiguity. Low uncertainty avoidance cultures feel much more comfortable with the unknown. High uncertainty avoidance cultures prefer formal rules and any uncertainty can express itself in higher anxiety. Table 2.4, adapted from Hofstede [11, p. 314], summarizes the effects this dimension that have implications to online learning environments. Table 3.3: Uncertainty avoidance dimension in traditional classrooms The dimension of uncertainty avoidance can affect how students perceive social affordances of the online learning environment. Also of importance are the effects of culture on the interpretation or an acknowledgement of the ambiguous data and judgment of the relevance of data in the unfolding interactional sequence. 3.2 Culture and Communication. 3.2.1 E. Hall’s Low Context vs. High-Context Communication Dimension Besides Hofstede‟s cultural dimensions model the dimension of “low-context” vs. “high-context” cultures introduced by Hall [16] are important in the contexts and situations of intercultural communication. According to Hall [16], in high-context cultures, usually the cultures with high power distance, a member needs to be explicitly asked to respond to elicit behavior that is a deviation from the norm. Table 2.5 lists patterns of Hall‟s cultural communication context dimension. Hall characterizes speaking as an art in high-context cultures, with an emphasis on the emotional aspect. High-context cultures privilege social motivation. In low-context cultures, by contrast, members expect to influence others to act by explicitly pointing out pertinent information. The information provided implicitly enables the communicating other to take the desirable decision. Low-context cultures privilege rational information. Table 3.4: Low-context vs. high-context cultural communication styles If the communicative context varies across cultures than it becomes a variable of interest in the learners‟ interactional accomplishment of problem solving. 3.3 Culture and Cognition. According to Nisbett and Norenzayan [17, p. 1], mainstream psychology in general had made four basic assumptions about cognition. Adapting from them, the four foundational psychological assumptions regarding human cognition are: Universality: Basic cognitive processes of sensation, perception, attention and memory are universal. In other words, basic cognitive processes are invariant across cultures and communities. Content Independence: Basic cognitive processes are invariant across contents. In other words, cultural differences in content do not affect the nature and structure of the basic cognitive processes. Environmental-Sufficiency: Cognitive processes of general learning and interference operate upon environmental contents to equip the child for functional survival. The environment provides content to cognitive processes without the need for cultural or social interventions. In other words, cultural differences in cognitive processes are due to different environmental influences and not social influences. Infinite Cultural Variance: Since the universal basic cognitive substrate is content independent and environmentally-sufficient, the range of cultures is a function of the variance in environmental conditions. In other words, cognition places no constraints on the possible evolutionary design space of cultures. All in all, these four assumptions have led to a belief in a fundamental dissociation between cognition and culture. One consequence of this was that psychology and anthropology evolved into independent academic disciplines with mostly nonoverlapping research agendas. However there were some exceptions to this dualist view of cognition and culture. These exceptions include in psychology, Lev Vygotsky and colleagues [18, see 19 for a biographical and historical treatment of this influential research movement]. In cognitive anthropology, most notably D'Andrade [20]; and in cognitive sociology, Dimaggio [21]. Recent empirical results have shown that culture and cognition are mutually implicated and are not disassociated as traditional psychology has postulated. 3.3.1 Nisbett and Colleagues’ Cross-Cultural Psychology Findings. Richard Nisbett and colleagues have embarked upon an experimental cross-cultural psychology research program to systematically investigate cognitive differences across cultures. Table 2.6, compiled from Nisbett [22, pp.xix, 44-45] and Nisbett and Norenzayan [17, pp. 21-25], presents a concise summary of above discussion along with empirical evidence from the literature. The cultural difference in attention to field vs. object is highly relevant to collaborative “knowledge map” learning environments. East-Asian learners might pay attention to a meaningful group of interrelated knowledge map objects whereas Western learners might attend to individual objects and evidential relational links. The cultural difference in attention can vary the ways in which referencing and deixis are carried out in collaborative discourse. East-Asian learners might make more references to regions of the concept maps and groups of related concept map objects (i.e., to fields of interest), whereas Western learners might reference individual objects in their collaborative discourse. This translates into a socio-technical design hypothesis that given the choice of referencing regions of concept map areas and individual objects in the concept map, East Asian learners will appropriate the affordances for referencing fields. On the other hand, Western learners will appropriate the affordances for referencing individual objects. Table 3.5: Cognitive differences between East-Asians and Westerners. The implications from the cultural difference in perception is that Western learners by virtue of being more susceptible to “primacy effect” might favor earlier perceptions of information related to a collaborative learning task. East-Asian learners might perceive more relationships between the information in concept map and instructional materials leading to a greater number of evidential relation links in the concept map. The cultural difference in causal inferencing processes implies that East Asian learners might be more inclined to reason-giving that prioritizes situational factors when compared to the dispositional attributions of Western learners. One particular implication would be the cultural effect on collaborative argumentation. Also, EastAsian learners‟ perception of their collaborative partners might follow this same trajectory. This might manifest as East-Asians‟ giving higher ratings for their collaborative peers due to situational attributions explaining any perceived unpleasant “performance.” Western learners might perceive their collaborative peers for their dispositional “competence.” This cultural difference in cognitive processes might manifest as East-Asian learners preferring a highly inclusive final conclusion in intercultural collaborative problem solving tasks. Western learners might argue for more differentiated analytical hypothesis that seems logically the most viable. 5. Discussion. Taking the existing body of research on cultural effects on social behavior, cognitive processes, online pedagogies and HCI, learning analytics should consider both appropriation of affordances (tool use) as well as technological intersubjectivity (how learners and teachers relate to, interact with, and form impressions of each other in technology enhanced teaching and learning settings). Given that both seminal networked learning research (Hiltz, 1994) and current online learning best practices prescriptions (Moore, 2006) emphasize student collaboration, and since these aspects vary across cultures in traditional classroom settings (Hofstede, 1986) as well as online learning settings (Edmundson, 2007), learning analytics should critically examine mono-cultural design assumptions. Learning environments and learning analytics solutions that do not incorporate diverse “alternates for action” might not achieve the best results in terms of student learning processes, outcomes and satisfaction. In order to exhaustively study the potential effects of culture on the appropriation of potentials for action and the negotiation of the meaning of those actions, one needs to analyze individual actions in the context of their interactional sequences [31]. Therefore, learning analytics tools should support micro-genetic analysis of learners‟ interactions apart from aggregating behavioral outcomes for statistical testing. Although the cognitive embeddedness of discourse and knowledge-building have been theorized and empirically evaluated [32, 33], social engagement and cultural embeddedness aspects of these design implementations have remained unexamined so far. Learning analytics designers need to consider ways of facilitating the varying degrees of social and cognitive embeddedness. Increasingly, issues are being identified in the cross-cultural implementation of online learning or e-learning systems which are primarily designed, developed, and evaluated in North America and/or Western Europe contexts [34]. To help remedy this situation, future work could investigate three models of cultural influence in online learning and learning analytics: (1) culture-specific, (2) culture-comparative, and (3) culture-interactional. Culture-specific work studies learning analytics in a specific cultural context where learners have a shared sense of identity. Culture-comparative studies investigate learning analytics processes and products across cultures. In culture-interactional studies, learning analytics in intercultural settings is the primary focus."