From the Guest Editors: Fostering intentional learning with technologies

Introduction

The researchers of the seven papers in this special issue of the Australian Journal of Education take different approaches and use various theoretical foundations to frame their arguments. Although diverse in nature, similar themes emerge which provide insights to enhance our understanding of intentional learning, and inform our practices in the use of technologies to foster intentional learning. Our aim in this special issue is to make a concerted effort to bring together discussions on the role of technologies in intentional learning.

Bereiter and Scardamalia (1989) suggested that learners are not only active in their construction of meaning but can also be intentional, which means that they are cognitively engaged in the learning process, monitoring, and regulating their learning (Sinatra & Pintrich, 2003). Taasoobshirazi and Sinatra (2011), drawing from Bereiter and Scardamalia (1989), suggest that an intentional learner is someone who uses “knowledge and beliefs to engage in internally-initiated, goal-directed action, in the service of knowledge or skill acquisition” (p. 210). Schnotz and Kurschner (2007) defined two different types of explicit learning. Incidental learning is learning without the intention to learn, while still being aware of what is being learned. On the other hand, when learning is intentional, the learner not only has the intention to learn but also possesses an awareness of what has been learned. Intentional learning is explicit when the learner acquires a specific set of target knowledge and when he or she is aware of and able to articulate what has been learned (Frensch, 1998; Kirkhart, 2001). Bereiter and Scardamalia (1989) used the term intentional learning to refer to cognitive processes that have learning as a goal rather than as an incidental outcome. It is an “achievement, not an automatic consequence of human intelligence” (p. 366). As put forth by Scardamalia and Bereiter (2006), intentional cognition is more than self-regulated learning; it is the “active pursuit of a mental life” (Bereiter & Scardamalia, 2002, p. 246), whereas self-regulated learning is usually a set of study skills and learning-to-learn strategies.

Technologies have the potential to foster intentional learning. Technologies can engage learners in the articulation and representation of their understanding (Jonassen, Howland, Marra & Crismond, 2008) and in the construction of knowledge. This special issue is an effort to bring together scholarly essays discussing research issues related to the use of technology for intentional learning. It aims to capture a wide spectrum of research in the use of technologies for fostering intentional learning and to inform future research in this line of inquiry. The manuscripts include significant reviews of the specific areas of focus and empirical findings to substantiate the arguments that are put forward by the contributors. The content of the manuscripts includes both theoretical and methodological issues related to the field.

The seven papers in this special issue are aligned with two themes: (1) Beyond the cognitive perspectives and (2) Technologies and intentional learning. The four papers written by Spector and Kim; Herrington, Parker, and Boase-Jelinek; Hanham, Ullman, Orlando, and McCormick; and Hung are aligned with the first theme. The three papers written by Lee, Rooney, and Roberto; Chee; and Murcia are aligned with the second theme.

Theme 1: Beyond the cognitive perspectives

Spector and Kim (this issue) argue for the importance of examining intentional learning through a holistic lens and discuss how non-cognitive aspects can significantly impact learning, especially complex situations such as problem solving and decision-making activities. The authors argue for the need to take into consideration an individual’s bodily and emotional characteristics and how they influence the individual’s perceptions and subsequent thinking. They discuss how non-cognitive factors such as emotions are critical in intentional learning. For instance, emotions can either disengage students from complex tasks or lead to resilience when engaging in challenging tasks. The authors then discuss how motivation and volition (refer to this issue for the definition) can lead to positive emotional experience and active engagement. It is interesting that Spector and Kim argue that volition can compensate for a lack of competence or confidence when exploring alternatives to solving difficult problems. In summary, the authors believe that volition can be learned and used to influence or manage an individual’s cognitive and non-cognitive processes. In the second part of their paper, Spector and Kim articulate a framework for engaging intentional learning with technologies, with a specific focus on volition. Although the authors recognize the need for a more comprehensive framework, it certainly is useful in that it provides ideas for possible implementation of technology-based learning for fostering intentional learning by taking into account non-cognitive factors. The authors also generate a number of useful research ideas in their framework. As identified by Spector and Kim, intentional learning implies the existence of learning goals, and learners in that context are rational agents who can make reasonable decisions.

Herrington, Parker, and Boase-Jelinek (this issue) explicate the above notion in their paper by highlighting the importance of reflection as an intentional and purposeful process that can be facilitated through authentic tasks. The authors refer to Boud, Keogh, and Walker’s (1985) definition of reflection as being “intellectual and affective activities in which individuals engage to explore their experience in order to lead to new understandings and improvements” (p. 19). Through qualitative research, Herrington, Parker, and Boase-Jelinek meticulously describe how the use of reflective web-based blogs and reflective examinations can facilitate pre-service teachers’ reflection in an authentic learning environment. Although the use of an examination may seem to contradict the authentic nature of the course, it was designed as an engaging reflective exercise. The authors found that the authentic tasks facilitated pre-service teachers’ in action and on action reflection, but reminded teachers to use reflective blogs to diagnose problems and provide necessary support for improving students’ learning. One key message from Herrington, Parker, and Boase-Jelinek is that reflection tasks need to be integrated intentionally throughout the entire course, encouraging students to constantly involve themselves in meaningful learning, echoing Spector and Kim’s notion of a holistic approach to intentional learning.

Hanham, Ullman, Orlando, and McCormick (this issue) raise the interesting idea of digital technologies functioning as a proxy in intentional learning. They further elaborate that intentional learners tend to strategically use technologies as a proxy to enhance their learning so as to achieve the desired learning goals. The authors then base their arguments on motivation theories to discuss the three key variables that influence students’ choice of technologies as a proxy. The three variables are learners’ achievement goal orientations, self-efficacy beliefs, and proxy efficacy beliefs. The contribution of Hanham, Ullman, Orlando, and McCormick’s theoretical model on intentional learning with a technological proxy agent is that it provides a detailed framework of how important non-cognitive variables influence students’ use of technology in the context of intentional learning. Such a theoretical model may be powerful in explaining the interactions between non-cognitive variables and technology as a proxy in intentional learning when validated through sophisticated statistical analyses.

In Hung’s brief paper (this issue), he provides a theoretical discussion on differentiating intrinsic and extrinsic intentional learning. All intentional learning events are a result of conscious decisions on pursuing an acquisition of certain knowledge or skills in order to accomplish a goal. However, the role of the learner in the decision-making process is critical in determining the intentional learning being intrinsic or extrinsic. Intrinsic intentional learning may be more robust and resilient in the process of learning than extrinsic intentional learning, especially when difficulties are encountered during the process. Hung also suggests that in facilitating students to develop a mindset for intrinsic intentional learning, guiding students to take a lead role and full responsibility in the self-evaluation and self-determination process. Technology that affords reflective processes or providing means for modeling will be beneficial for facilitating students’ development of intrinsic intentional learning.

Theme 2: Technologies and intentional learning

Chee’s (this issue) paper is deeply grounded in philosophical arguments. He argues that the notion of intentional learning has been typically construed from a perspective that foregrounds cognitive engagement and mental life in meaning making. He then challenges this view and argues that a theoretical positioning based on the dominant paradigm of human information processing psychology leads to incoherence because this paradigm results in “meaning-less cognition.” Chee discusses a reconstructed view on intentional learning from the perspective of Deweyan inquiry and the philosophy of pragmatism, and situates this reconstruction in the context of empirical research on game-based learning as he argues that intentionality emerges from the action–reflection dialectic in situated learning. He explicates his notion of intentional learning by describing a Statecraft X game in which learners engage in collaborative problem solving and decision making.

In Lee, Rooney, and Roberto’s writing (this issue), they discuss the dimensions of intentional learning and identify the key benefits of systems modeling with regard to intentional learning. The authors then describe a technology-enhanced learning environment that may foster intentional learning. In the first part of their paper, the authors argue that for intentional learning to occur learners must realize the need to learn and the value in learning, and they do so possibly through everyday problem solving and learning which must encourage regulation and monitoring of learning. The authors also argue that for intentional learning to take place, learning situations must provide opportunities for learners to be cognitively challenged and provide a platform for learners to realize the inconsistencies between beliefs and understanding. Through a web-based scaffolded systems modeling tool (PRES-on), the authors propose systems modeling as one of the most engaging activities that helps learners build systemic thinking, domain knowledge, and possibly invokes conceptual change.

Murcia (this issue) takes a slightly different angle when looking at intentional learning as she discusses the notion of intentional teaching which includes pedagogical practices that are deliberate, purposeful, and thoughtful, involve interaction between students and teachers for the building of knowledge, and involve pedagogy that incorporates technology. Based on the multimodal representations affordance of Interactive White Boards (IWB), Murcia argues that it can be used to scaffold the construction of scientific understandings, explanations, and reasoning. Through case study research, Murcia describes the use of IWB in primary science classrooms and concludes that when supported with technology, IWB in this case, intentional teaching can promote higher levels of thinking and conceptual engagement.

Intentional learning in the context of technologies

The definition of intentional learning was briefly discussed by various researchers. Based on the previous discussions on intentional learning, the authors in this issue further explore and explain the term intentional learning. What is most encouraging and exciting is that the term is not only expanded, criticized, and reconstructed but is also intricately linked to technologies. In the spirit of constructivism, the concerted effort of refining the key term brings forth new perspectives for understanding intentional learning.

All of the authors in this issue would agree with previous researchers that intentional learning is effortful and goal oriented. However, some authors in this issue have further expanded the term. For instance, Lee, Rooney, and Roberto (this issue) suggest that an intentional learner is someone who wants to learn, sees the need to learn, believes in the need to learn, knows what to learn, knows what is needed to learn, and knows how to learn. They also argue that there is a need to reconsider what it takes to be an “intentional learner” from a more systemic perspective, and discuss the various dimensions of intentional learning. The authors then propose that given the nature and benefits of systems modeling, it best explicates intentional learning as a form of instruction. Hanham, Ullman, Orlando, and McCormick (this issue) raise the idea of technologies as a proxy which can be used by learners in ways that enhance their opportunities to fulfil the goal of learning and in ways that do not. Chee (this issue) re-constructs the definition of intentional learning and argues that intentionality emerges from the action–reflection dialectic in situated learning. He further illustrates his argument by describing the Statecraft X multiplayer immersive game. Murcia (this issue) offers a different perspective on intentional learning. She focuses on intentional teaching by suggesting the purposeful pedagogical practices involving interactions between students and teachers and the incorporation of technologies in such interactions.

Implications for the design of intentional learning

Throughout all of the papers in this issue, the authors either implicitly or explicitly discuss the importance of problem solving in their arguments. They do so by acknowledging the importance of a systematic approach towards not just understanding what intentional learning entails, but the instruction to propel intentional learning. For instance, Hung (this issue), who builds on Bereiter and Scardamalia’s (1989) analogy of intentional learning as a problem-solving process, states that during such a systemic inquiry learning process, the learner identifies what needs to be learned, the learning gap (problem space), activates his/her prior knowledge and schema, and refines or restructures the conceptual framework. Similarly, Lee, Rooney, and Roberto (this issue) state that situating students in everyday problem tasks provides them with the avenue to realize the need to learn and the value of learning, thereby engaging in intentional learning. Specifically, problem solving as a learning strategy can increase students’ awareness of the inconsistencies between their naive theories and those that are scientifically accepted, and create intentional learning opportunities that arguably avoid the development of confused synthetic models (Vosniadou, 2007a, 2007b). Chee’s (this issue) Statecraft X game also provides learners with the opportunity to collaboratively solve problems and make decisions. Herrington, Parker, and Boase-Jelinek (this issue) propose the use of authentic learning pedagogy as it provides students with opportunities to solve real problems like professionals. Spector and Kim (this issue) also make the point that non-cognitive factors can influence problem solving and decision-making processes because they not only require a meaning-making activity but also imply a conscious intention to resolve the problem or reach an acceptable decision. Given the important role problem solving plays in intentional learning, educators when designing learning should perhaps seek to integrate authentic problem solving tasks at the cognitive as well as non-cognitive levels. To promote awareness of wanting to learn and of understanding the value of learning, the embedded problem-solving tasks must resemble as closely as possible those found in real world settings and be integrated throughout the whole course of study. It is also worth noting that intentional learning requires highly self-directed learning processes and skills, as rightfully pointed out by Hung (this issue); hence, necessary scaffoldings have to be considered in designing problem-solving activities for intentional learning.

Conclusion

The papers presented in this special issue take different approaches and theoretical foundations to frame their arguments. Although diverse in nature, these writings provide insights that enhance our understanding of intentional learning and inform our practices in the use of technologies to foster intentional learning. The arguments in these papers have parallels in those found in student-centered learning research. However, the powerful role of technologies is very much explicated and emphasized in this special issue.