Technological equity

One of the key concerns about the use of technology is whether it is able to serve all populations of people in such a way that it allows them to achieve valuable functionings  (Sen, 1984). I won't go into detail into Sen's argument here, since I am using capability approach as a way to discuss Warschauer's (2008) analysis of the digital divide.

So what does economics have to do with technology? If one were to use Warschauer's (2008) argument that lack of access to information and communication technology (ICT) is a causal factor in impoverishment, then it is clear that technological access impacts economical well-being, and in turn, an individual's quality of life. However, an understanding of access has to include factors other than physical or infrastructural capabilities. For instance the Enhancing Education Through Technology (EETT) report highlights how physical, digital, human and social resources interact in order to address the issue of access. While  the report acknowledges the role of social resources, there was no analysis regarding the forms of support available for students and teachers. Student literacy was also not examined since it was not within the scope of the report. Thus, although the report presented some useful trends, it did not allow us to understand how students and teachers are using ICT or their capabilities. This gap is arguably bridged by Warschauer (2008), who offers evidence of how technology is used unequally by students of low and high socioeconomic status. Volman and van Eck (2001) on the other hand, offer a further nuanced overview of inequity by including a discussion of how technology impacts gender. In contrast to Warschauer, these authors argue for a fine-grained understanding of use of specific ICT applications according to students' approach towards ICT use, their level of participation and outcomes of this participation.

In terms of my model, I have focused primarily on Warschauer (2008), as well as Volman and Eck's (2001) articles as a way of expressing how certain factors can impact access, and in turn one's level of participation, approach and outcomes. At the micro-level, one can examine the teacher-student-object interaction, whereas the expanded aspects of the interactions include other factors that impact these interactions. To date, I have not made changes to the basis of the model since several revisions ago, primarily it serves its function as a theoretical model that explains interactions between actors within the structures of the world.

Virtual worlds

Ah, virtual worlds. The key argument put forth by Steinkuehler & Duncan (2008), Neulight et al (2007) and Hudson & Degast-Kennedy (2009) is that the learning (be it content, dispositions, etc.) gained from virtual worlds is potentially transferable to real life learning situations. Steinkuehler & Duncan (2008) argue that scientific habits of mind may occur in the wild while Neulight et al (2007) demonstrate that designing for virtual worlds can be beneficial for students but remain challenging for learning. Regardless of methodological issues present in the former study, it stands to reason that some players engage in scientific literacies. A bigger question for me is thus who is participating, since it may very well be that only interested players would visit such forums in the first place, as opposed to a classroom environment where students have limited choice in their participation. This is not to say that the students did not enjoy Whyville, although there seemed to be healthy skepticism among the participants in Hudson & Degast-Kennedy's (2009) study.

What does this all mean for educators and researchers interested in using such technologies in the classroom? For me, the big takeaway from these authors is the role of the teacher and curricular design. Neulight et al (2007) highlighted that learning gains are impacted by these two factors, a message that I think is consistent across all the literature read thus far. Nardi and O'Day will certainly agree that in order for effective learning to occur, educator must understand how individual components of a learning ecology interact. To this effect, my model remains unchanged, but I have illustrated the model with problematic components to illustrate why learning gains in the Neulight study were superficial. Through this illustration, I hope to present justification as to why taking into account components of the model is necessary for learning and demonstrate the usefulness of the current model.

Computational literacies

If there are multiple views on what counts as literacy, there seems to be a range of views on what counts as computational literacies in the fields of science, media and computing. While not specifically focused on the notion of computational literacies, Peppler & Kafai (2007) recognize that youths must be able to participate in new media cultures by "learning the [necessary] visual, semiotic, aural and technological literacies" (pg. 5). Scratch, a programming tool, presents opportunities for youths to participate by creating digital productions. One can argue that the representational form underlying the literacies being supported by Scratch is concrete in nature, as opposed to the abstractions underlying diSessa's (2000).

Wing (2008) characterizes the ability to operationalize abstractions and understand the relationships across multiple layers of abstraction as computational thinking, or arguably, as computational literacy. He contends that this form of computational thinking is useful across multiple disciplines such as economics and biology. Such a claim however, needs to take into account the basis of the representational forms that underlie specific genres and their social niches (diSessa, 2000). But what exactly is the representational form that underlie computational thinking or Boxer for that matter (Sandoval, 2001)? Could the box model, even if abstract, serve as a basic notation system that can affect other genres and social niches? How does abstraction work as a principle, and is there an underlying model that we can use to understand different forms of media? How does abstraction help us understand the fundamental representational form of Scratch, which is quite concrete?

To address these questions, it is perhaps useful to take into account what abstract and concrete representations do for learners. It may very well be that abstract forms of representations may be instrumental for experts, whereas novices learn better with concrete forms of representations, but a combination of both concrete and abstract is arguably present in both Scratch and Boxer. The degree of abstraction and concrete however varies tremendously, largely because there is no single model that informs the creation of notation systems. I'm unsure as to whether this interpretation is valid, and more thinking is definitely required to make sense of literacy in general.

In terms of the model, diSessa's pillars of literacy can be embedded as part of the lifeworld; the material, social and cognitive aspects of literacy is relevant to how individuals think about being literate and how objects are imbued with these affordances. Note that the 3 aspects of literacy maps on to Bourdieu's (1986) forms of capital; economic, social, cultural (note that individual disposition or habitus is a culmination of these 3 factors according to Bourdieu). I have not changed the basic design of the model, but have instead used the model to illustrate how one may think about literacy by using the model.

Mobile technologies

Mobile technologies are powerful tools that allow individuals to immerse themselves into authentic scientific inquiries that will potentially lead to learning (Colella, 2000; Klopfer, Yoon & Rivas, 2004; Squire & Klopfer, 2007). While virtual learning environments may allow learners to explore these spaces through the use of an avatar, by interacting with simulations or with instructing teachable agents, learners are confined in a physical space, usually the computer laboratory. Colella (2000) notes that participatory simulations, or "life-sized, computer-supported simulations" (pg. 471) are microworlds that have underlying rules that constrain a user's actions. Participatory simulations moreover allow students to construct an understanding of the world by using their intuitions (Klopfer, Yoon & Rivas, 2004) and create a safe space where students can potentially learn from their failures (Squire & Klopfer, 2007). While the potential of mobile technologies are important, the lack of feedback and scaffolding may impact students' learning, as demonstrated by Squire and Klopfer (2007). While the idea of a sandbox may be interesting, free play in participatory simulations is arguably similar to the concept of pure discovery learning, where students receive no guidance from the instructor (cf. Mayer, 2004). In contrast, Colella's (2000) analysis of the disease simulation underscores the importance of framing these activities in a way that students are able to make sense findings although there was no analysis of the impact of researchers and facilitators in guiding student understanding. Regardless of these findings, mobile technologies can indeed be powerful learning tools, if designed carefully.

Model 3.1

With this in mind, I have not updated the old model, because I believe that it is still able to explain the interactions within this particular system/ecology. However, I have explicated certain aspects of the model and created two separate Participatory Simulation models which illustrate the interactions between students. In particular, I used Bourdieu's (1986) concept of capital to explain how aspects of our lifeworld or our interpretations of our experiences are influenced by not only by our individual characteristics but also by other structures that exist independent of us (e.g., economy, educational qualifications, class, race, gender, etc.). This is a vital component to explicate because our interactions with others and objects are influenced by our lifeworlds, but the lifeworld is also changed through our interactions with others and objects. Objects themselves are not value-free; what we see of things in the world dictate how we interact with them. The designed mobile technologies for instance are value-laden objects that have to be unpacked by students. At the same time, the role of the instructor cannot be taken out of any learning situation, if one wants to achieve better learning (see model 3.2).

Model 3.2

The elaboration of lifeworlds moreover, is useful when one tries to understand how a female student would approach mobile technologies, in contrast to a male student. Note that the outcome of such interactions affect our ways of thinking and being, which can be thought of outcomes or goals for a given activity. Using Klopfer, Yoon and Rivas' (2004), findings about increased students learning, the model illustrates that despite an apparent difference in attitudes towards games, females experienced learning gains, comparable to their  their male counterpart, as illustrated in model 3.3. Thus, we are able to focus on aspects of the object or activity design that may have resulted in this gain. Currently, the model is unable to pinpoint the various aspects within the system/design that has to be changed, but given that its focus is on the interactions between individuals and objects, perhaps another model or revision may be in order. Suggestions and feedback regarding this is welcomed!

Model 3.3

From the macro to the micro

If the previous readings (Nardi & O'day, 1999, etc.) can be categorized as reminiscent of a macro-analysis of the way that individuals interact with technology, Enyedy (2003),  Koedinger & Corbett (2006) and Schartz et al (2007) present a micro-level analysis of the interactions between individuals and technology. I borrow the terms micro and macro here from sociology to distinguish the analysis of systems and cultural structures from the analysis of everyday social interactions (in some sense, the individual acting within the system). In fact, the classroom is a locus of everyday social interactions. In the micro analyses presented by  Koedinger & Corbett (2006) and Schwartz, Blair, Biswas, Leelawong & Davis (2007), the authors focus on individual structures of thinking (schemas) and recognized the taken-for granted influence of social interactions on individuals cognition to a limited extent, or not at all (Schwartz et al. were arguably more overt in this recognition). Enyedy (2003) on the other hand, understood learning as social practices, or culturally-derived standards of behavior. Additionally, he argued that learning extended beyond the individual-social dichotomy, acknowledging that meaning (or learning) is "interactionally co-constitued" (pg. 365).



Given the interplay between the agency-system and mind-social dichotomies that arise in these articles, I have sought to revise my model by acknowledging that the nature of the lifeworld as inter-subjective, in which experiences are social in nature and can be shared with others. For instance, the interaction between peers and/or teachers are intersubjective in that each party comes with their own interpretation of the situation and affect each other's interpretation of the situation before them (recall Schwartz et al.'s example of the mother and child interaction). In some student interactions with technological designs on the other hand, students are in effect interacting with the embedded intention of the designer (e.g., cognitive tutors). Successful learning as such, depends on the perceived affordances of the designed technology. Perceptions of affordances however, are drawn from the lifeworld, as well as the presence of others. As noted by all the authors, successful use of the technology used in the classroom depended on social interactions with peers and teachers.

As I reflect on the model further however, perhaps there should actually be another thought-bubble that arises from the subject-object interaction, since this interaction affects how each would be thinking/thought of. Here, objects are taken to mean as artifacts that are imbued with cultural meanings drawn from one's lifeworld. They are thus not neutral, but instead imbued with a variety of meanings. Admittedly, the model is still general, but does capture the various aspects that are important in understanding the role of subject and objects in relation to the lifeworld (structures and systems included!).

Person-Lifeworlds-Technology versus Information Ecologies

A common theme among the three papers was the nature of technological affordance and in particular, how these affordances depend on the interaction potential of users (Stahl & Hesse, 2009). Interaction potential in this sense refers to users' ability to perceive the constraints and possibilities in the activity and environment (Gibson, 1977). This echoes the other authors' argument that a shift of perception is necessary in order to understand technology and for users to be critical and reflective of the corpus of information found in information ecologies, as well as being aware of the invisible  practices and working styles present in such ecologies (Burbules & Callister, 1999; Nardi & O'day, 2000).

Model Version 1.0

The original model I had about the role of technology in education leveraged affordances as a heuristic about how to think about the role of technology in our lives. It was general, and purposefully so, since I wanted to focus on the dialectical interaction between person and environment, as well as what Husserl (1936) characterizes as our lifeworld. While the concept of lifeworld is complex, I use it here to represent both one’s personal attitudes and the sociocultural established meanings given to experiences and/or interactions with objects or persons in the world.

Model Version 2.0

In the updated model, I have chosen to specify the components of the interactions among individuals, their lifeworlds and technology. This model mirrors Nardi and O'Day’s (2000) concept of information ecologies to a certain extent. Nardi and O’Day make a compelling argument for the concept of information ecologies; local environment with various practices, values, technologies and people. These ecologies encapsulate the three metaphors or holistic assumptions and questions regarding technology as tools, texts, and systems.

Much like information ecologies, the concept of lifeworld allows us to understand the impact of lifeworld on individuals and can be further operationalized into the existing material and symbolic aspects of the human condition.  Drawing on this model, the interaction between person-lifeworld-technology can impact one’s use of material technology (as a tool) and the intention and symbolic meaning embedded in these interactions (as text) and represents the magnitude and scale of the role of technology in our lives (as a system). Nardi and O'Day presented a good overview of the complexities involved in the idea of systems, but I found it undefined and problematic since it did not seem as if the ideas were synthesized usefully. I have chosen here to define system as the replicated relations between actors which are in turn structured as social practices (Giddens, 1984).

To illustrate this model, I have selected the gaming ecology in a World of Warcraft raid instance. The raid instance represents the technological world of an online gaming environment, complete with various tools and interactions with others which are necessary for the success of any given encounter. Players must not only know how to use the material aspects of the technology, but must also pay attention to the interpretation and meaning of symbols embedded in the local environment, which functions as an enclosed system. Simply put, a person's interaction with the designed game environment (which represents technology) is informed by her lifeworld, which in turn affects her gameplay and the uptake of the technology. This lifeworld can  consist of the norms associated with what it means to play a certain class, the practices associated with the group that one belongs, but can also be affected by the lifeworld of others. On the other hand, the existence of the designed game environment presents constraints and affordances and thus changes how people interact with one another.

As I ponder on this model however, it seems to mimic Marx’s conceptualization of human society as consisting of the base (technological and social forces of production) and superstructure (beliefs systems/practices). This is not necessarily a surprise, given Marx's influence in dialectical materialism, but certainly leaves more room to explore the model currently represented.