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Continuing write the research essay based on existing 1300 words. My assessment is a 2500 words critical analysis and reflection based on my group work, and proofreading.Requirement: Critical analysis and reflection on the design process and its outcome based on the design case group work.Describe, support with literature, and critically reflect on your design case. More information about the requirement, design method journal, the example given by module, etc. I will ATTACH ALL, please read carefully before you start, thank you!!! ：） _example.docx _example.docx assignment.docx design_case_ppt.pptx week_3_6_group_discussion.docx Unformatted Attachment Preview PART A Introduction Our group opted for a very demanding, but even more interesting topic, which is self-regulation. The exact problem we finally ended up addressing was how to support self-regulated learning in collaborative contexts. We did not come up with an actual tangible technological tool, due to limitations and deficiencies on which I will elaborate later in this essay, but we managed to create a very concrete and justifiable design path to be followed for a self-regulation technology. Design Case Self-regulation is an issue that has lately been drawing a lot of attention. In the educational domain, it can be defined as an active process during which learners plan, monitor and reflect not only on their learning, but also on their motivation and emotions (Law, Ge and Eseryel, 2016). Educational settings are now being revolutionized by the idea that learning content is not the educational objective anymore. The ultimate goal of education now is, or should be, to enable students apply their learning skills in any new situation they will have to face. The goal of education is now the preparation for future learning (Stanford, 2016). One could argue that self-regulation is an indispensable part of the above educational revolution, while it addresses students metacognitive ability to become fully aware of how they learn, or how to teach themselves. Indeed, self-regulation encompasses a variety of behaviors, such as selfcontrol, which are foundational for generalizing individual learning techniques to new contexts and situations (Oreck, 2004). Hence, supposing that learning consists of a cognitive level and a metacognitive one, the domain knowledge we used to create our technological tool, addresses the metacognitive level. Metacognitive knowledge includes monitoring of ones learning, performance and cognition (Azevedo, 2013). Metacognitive knowledge is achieved when a set of metacognitive subskills is realized (Oreck, 2004). Two skills that function at the metacognitive level of human mind and play a significant role at the realization of self-regulation are self-awareness and emotional awareness. To clarify, emotional awareness and self-awareness enable learners monitor and control the effect of emotions on their performance, set goals and behavioral intentions (Lin, Fan and Chau, 2014). On top of that, one of the most important characteristics of self-regulation, which also played a major role in our design, is its cyclical nature. Learners are involved in a repetitive, self-reflective process during which they generate thoughts, feelings and actions and, after receiving feedback, they reflect on them and re-adapt them, in order to reach their personal goals (Zimmerman, 2000). These changes are re-adaptations that appear to be critical to the development of self-regulation, because behaviors, thoughts, feelings and even knowledge, change and improve during the course of learning. In our design we aimed to address a research gap regarding selfregulation, which is related to collaboration. Collaborative self-regulation has been proved to have beneficial outcomes but has not yet been thoroughly examined. Research has shown that a deficiency or malfunction in social learning experiences can provoke self-regulatory dysfunctions (Zimmerman, 2000). As Vygotsky has also emphasized, the social environment plays a crucial role in creating contexts, influential to any type of learning process, such as the acquisition of self-regulatory skills. It is true that until now, most research has focused on the individual and not on the student as part of a community of learners. (Beishuizen and Steffens, 2011). The research that has been conducted in the area of co-regulation has proven that when students work collaboratively, their self-regulation skills can increase. Providing students with the opportunity to develop co-regulation skills, entails the potential to improve learners self-regulation (DiDonato, 2013).Hence, co-regulation, the ability to monitor others, provide and receive feedback, understand and examine their thoughts and intentions, will be taken into consideration in our design as a transition stage, after which, the learners can reach self-regulation while they collaborate. It is true that selfregulation entails the cognitive dimension, the metacognitive dimension, but also the social dimension, which has to be further supported (Law, Ge and Eseryel, 2016) The importance of such a technological tool lies on the fact that selfregulation is considered an important skill to be developed not only for low achieving but also high achieving students. Both of them are prone to experience motivational and achievement problems and selfregulation appears as a potential solution to overcome these problems (Livingstone, 2012). Moreover, the process of acquiring self-regulatory skills plays an essential role in creating the students identity as a learner. Our target age group is early secondary students, as well as their teachers. At first, our aim was to compare face-to-face and online students, but during our journey through the module, we realized that the emphasis should be given on face to-face collaboration alone. Given that coregulation emerges as necessary to the development of self-regulatory skills in collaborative situations, and since co regulation depends a lot on gestures, facial expressions, dialogue, argumentation and action, it would be better facilitated by the physical presence of all group participants. Hence, in an effort to keep our design simple but more concrete, functionable and efficient, we narrowed our participants down to the face-to-face group. Theoretical underpinnings Given that our challenge was to improve self-regulation, which is an individual skill, in a collaborative situation, the learning theory that would best fit our design is constructivism which falls under the socio-cultural model of learning. Adapting a Vygotskian perspective, sociocultural approaches highlight the interrelation between individual and social processes to the construction of knowledge (John-Steiner and Mahn, 1996). The cultural and social context play an important part in learning and development. Hence, constructivist instructional technologies, like the one we were aiming to design, facilitate personal improvement through experiences and interactions with others, by creating situated and novel ways of understanding (Cox, 2008). As a result, following the theory of constructivism is the best choice which allows the creation of a group situation and the examination of self-regulation skills through interaction. The instructional goal of constructivist technologies is to support knowledge construction, rather than knowledge communication, to offer authentic and learner-centered tasks, entailing reflection on experiences and intrinsic motivation. The role of the teacher is not eliminated but changed, while he/she functions as a guide and not as an expert. The knowledge type we aim to address through our technology is epistemological knowledge. Epistemological knowledge is knowing about knowledge, which perfectly fits the metacognitive learning skills we aim to improve. It consists of sub categories, from which, the most useful for our design, are strategic and situational knowledge (De Jong and Ferguson-Hessler, 1996). Situational knowledge is knowledge about the situations that emerge in a particular domain. Since context plays such an important role in our design, situational knowledge would be essential for the development of self-regulatory skills through collaboration. Strategic knowledge helps students monitor and organize the steps they should take to solve a given problem or a task. This type of knowledge is more than necessary not only for self-regulation, but also for co-regulation and collaboration. Design Rationale In our design, we decided to use Knowledge Representation (KR). When we first started thinking about our technology, we decided to create an intelligent system. Without having something concrete in mind, and after a lot of thought and discussion, we agreed that the first step we would take is to have a knowledge representation for this intelligent system. According to Szolovits, Shrobe and Davis (1993), KR is an expression of an intelligent reasoning that represents the fundamental conceptions of this reasoning and how they are related. As he proposes, KR is a semantic map that aids efficient computation, while it guides the experts on how to categorize information and produce a tool that accomplishes the required steps and inferences. What is very critical about KR, which we also used as a guide when trying to depict ours, is that we should not confuse the representational choices for KR, with data structures. Before having the actual data structure, one should create a semantic diagram that carries the meaning of concepts we want to convey. This is the KR. However, during the process of thinking our KR, we encountered a problem. Self-regulation, as also mentioned above, functions at the metacognitive level. Thus, since our domain knowledge, the skill we aimed to teach was self-regulation, we should find a cognitive level, on which we would base the activities of our design, which we should then give to students to work on. At first, we decided to have the cognitive level of second language acquisition and create a tool that teaches selfregulation through second language acquisition activities. We eventually diverged from this idea and the reasons will be explicated later in this essay. Therefore, our conclusion was that we should create a KR for selfregulation skills. Winne (2015), has proposed some phases to reach selfregulation, which we slightly altered according to our goals and adaptations for our KR. In Phase 1, the learners make decisions regarding factors that could influence their learning and they set their goals and make some initial strategic decisions. In Phase 2, they make decisions on how to achieve those goals, they gather and filter information. In Phase 3, the learners interpret the information, start asking questions to monitor their own learning and progress so far and adjust their strategies. In Phase 4, we have added a collaborative stage and self-assessment through offering and receiving feedback. Those four phases take place reciprocally. Finally, there is the final Phase 5, of reflection and metacognition, where the initial self-regulation takes place. However, as mentioned above this is a constant cyclical process which should be repeated according to given feedback, in order to reach the final selfregulation. This cyclical process is represented in the following figure: At the next stage we decided to include participatory design. This designs goal is to take into account the users perspective and reflect it in the design of the technology (Cocea and Magoulas, 2015). In order to inform our design, we decided to apply knowledge elicitation techniques. More specifically, a human-tutor example would provide us with rich information on some aspects of our design. For instance, we encountered a paper from McQuirter Scott and Meeussen (2017), in which a teacher was teaching self-regulation skills to her students in her classroom. This situation helped us raise questions like “How can our technology replace the role of the teacher in scaffolding? or How can our technology provide feedback to students?. To elicit the above information, we would apply techniques like classroom observations, video recording analysis and questionnaires. After eliciting knowledge from the teacher student interaction, we decided to include a participatory phase with the students. This stage aids the learner modelling process. Part of our design would be an intelligent learner model, while such technology allows the system to adapt to individual needs and interacts with individual learners (Cocea and Magoulas, 2015), a process that seems necessary as one of the methods of addressing the development of self-regulation skills. As designers, we viewed participation as a mutual-learning process, during which both the designers and the participants are positively affected (Halskov and Hansen, 2015). From our perspective, the participation of students and teachers would provide us with information on how to develop our tool eventually, according to their preferences and needs. From the participants perspective, both teachers and students would acquire experience on aspects of technological design. At the same time, given that our learning objective is self-regulation and that the design process involves testing ideas, brainstorming and implementing initial prototypes, they would also acquire domain knowledge on how to test their teaching skills and self-regulation skills, accordingly (Good and Robertson, 2006). Our next step would be to apply user-centered design to the process. User-centered design addresses the end-users of the product, which in our case are again both students and teachers and facilitates an iterative design process in which the end users influence the shape of the final design, by providing the designers with meaningful feedback (McLoone et al., 2010). For instance, after creating a prototype of our tool we could test the usability of our technology by asking teachers and children to use it. This step would give us feedback on technical as well as more commercial characteristics of the output, like the appearance of the interface and how it appeals to the end-users. The application of user centered design would be essential to finalize our design as efficiently as possible, because this process would help us evaluate its usability and functionality by applying the structure in a real classroom situation and re-design it until we reach the final product. Reflection After a lot of thinking and discussion, and since our domain knowledge is self regulation, which addresses students metacognitive level, we came up with the solution of creating a design that would not be applied only to second language acquisition contexts, but to any learning context. This is one of the biggest strengths of our design-thinking process for our tool. Moreover, I believe that our design thinking process is quite lucid and clear and could properly guide a programming expert to come up with a tangible tool which we do not have the knowledge and expertise to imagine. Such an effort to develop an actual product for our goal would be more than meaningful because self-regulation fosters the differentiation of learning by addressing individual student needs and collaboration appears as significant to trigger students motivation and better learning outcomes. However, one of our designs most critical weaknesses is that we did not come up with a particular and tangible technological tool. The only aspect which we were able to identify is the existence of an intelligence system that would be able to support orchestration within the classroom and facilitate teachers classroom management. In fact, one of the most critical limitations and difficulties that we faced throughout the whole process is the complexity of our design case, which consists of two layers, a cognitive one and a metacognitive one (Bruin and Gog, 2012). Thus, this challenged our effort to create a piece of technology and provoked many obstacles, both at the theoretical level of knowledge representation, knowledge elicitation and design processes, and at the practical level of being able to imagine and present a tangible tool. As a group, we spent a lot of time trying to figure out on which level our focus should be placed, and thus we run out of time for focusing on the actual tool interface. Finally, the design case itself challenges the creation of the technological tool. The initial goal we set, to entail in the tool both a cognitive level, like ESL, and the metacognitive level of self-regulation, was very far-fetched. This is the reason why we managed to focus only at the metacognitive level and provide some decent and in-depth guidelines for a potential design, instead of coming up ourselves with a proposal of a technology. Part A: Critical Analysis of the Group Design Process For our group project, we initially chose self-awareness as our design case, with a focus on exploring the difference between face to face interaction and online engagement for young learners development of self-awareness. We chose this theme collectively, considering our general interests across the design case options. This democratic decision process aligned with our shared theoretical position within an interpretivist paradigm and an ontology of relativism, where truth is a consensus formed by co-constructors (Pring in Scotland, 2012: 12), as well as with social constructivist theories of knowledge construction. We initially focussed on investigating how group awareness might affect the development of the self-regulated learning (SRL) skill of children aged 12-14 years old. Although there may be great differences between children of the same age in terms of their self-regulation ability (Wigfield, Klauda & Cambria, 2013), we believed this age group would be appropriate as young people around this age may begin to develop more nuanced social skills and negotiate knowledge of the self, though this may be dependent on specific socio-cultural contexts (Shaffer, 2000; Vygotsky, 1978). In this sense learners of this age group, as they approach adolescence, may experience more tangibly an awareness of the social negotiation of learning (Scardamalia & Bereiter, 1991). Therefore, we believed our design would be especially helpful for this age group. After some discussion, we were concerned our approach might require a positivist design, in order to measure the variables for the two conditions (face to face and online), therefore requiring a quantifiable measurement of the different levels of mutual or selfawareness skills. Due to our interpretivist, relativist position, we therefore, shifted our focus from attempting to measure these skills as competencies, to a socio-cultural model of learning, wherein learning is a less rigid phenomenon that happens between people, not just in the mind (Scardamalia, & Bereiter, 1991). Furthermore, we envisioned that learners might construct knowledge through an existential matrix of sensory input, experience and reflection in a social-cultural context (Dewey in Maddux & Donnett, 2015), where knowledge emerges from an intentional process of creating connections between actions and consequences (Xyst, 2016: 16). Therefore, we focused on the possibilities for supporting the development of mutual and self-regulation through social constructivist learning situations, consistent with our epistemological orientation as co-constructors. As a result of discussing methods to support the development of self and mutual regulation, we decided to focus on self-regulation (SRL). We realised we were interested in providing a situated learning context as a conduit to support the development of SRL skills, using a socio-cultural learning model. We also wanted to incorporate constructivist theories concerning the situativity of knowledge acquisition, via active learning strategies, which consider the context and culture in which knowledge occurs (Durning & Artino, 2011; Tobias & Duffy, 2010; Vygotsky, 1978). Initially we were distracted by technological features, rather than purpose. This changed as we were introduced to knowledge representation and knowledge elicitation as design approaches, as well as contemplating texts that were presented. For example, Kirkwood and Price (2014) highlight the importance of determining the purpose of educational technologies, which is especially important considering the contested agency of technology for enhancing learning directly (Selwyn, 2 ... Purchase answer to see full attachment