Technology Education (Personal Essay Sample)

Personal Learning Goal Assignment

Draft Learning Objective

My learning objective is applying Cognitive-Based Affective User modeling approach to learning in Game-based Learning (GBL) environment. This objective builds on theme two: Philosophy of Educational Technology. It has been established that GBL is interactive and enhances the flexibility of instruction in an online learning environment, and that during such sessions positive experiences mostly depend on personalized instruction approach. My interest in this objective can be attributed to its emphasis on examining the effectiveness of learning from the cognitive theory approach, which directly targets human psyche.

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It is also clear that student modeling often focuses on effect. This is done in three ways: first, an instructor recognizes the effect of physiological processes on emotion; second, the instructor follows the perceived emotion to its origin; third, the instructor combines the first and the second approaches (Bashar et al., 2010). Unfortunately, the success so far has been based on laboratory settings, which are the least associated with an educational setting.

Now, the control-value theory holds a different notion as opposed to the one mentioned earlier. This theory supposes that appraisals of both control and value are core to examining emotion (Brave & Nass, 2008). So, according this learning objective, I would be implementing and evaluating an emotional student Control-Value Theory, which builds from the second approach in its application to online GBL environment. Implementation is done using Bayesian networks, which consist of dynamic sequences applicable to online learning environments.

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Learning Plan

It is no doubt that both Virtual Learning and Game-Based Learning (GBL) have become promising ways to give formal instruction with higher levels of flexibility and interactivity that incorporate the idea of student’s preferences to promote student’s learning as well as engagement (Moore, Dickson-Deane, & Galyen, 2011). A typical GBL environment consists of sound effects, feedback, and storytelling, which often serve to enhance the emotional connection between the instructor and the learner . The key to reaching this ultimate goal in a Virtual Learning and GBL environment is to be able to personalize instructions for students as has been found by researchers Jansen, van den Broek, and Westerink (2011). To achieve both goals, my plan will be to adopt a GBL environment for teaching and learn physics – PlayPhysics.

PlayPhysics will be essential in acquiring data that relates to how students interact with a GBL environment and, thus, are enabled to express their emotions well. The reason why I choose PlayPhysics as the basis to my plan is that this GBL environment includes emotional student model (Munoz et al., 2013), which will be invaluable in testing my hypothesis.

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It is also clear that PlayPhysics platform has been widely applied and tested for students at higher learning institutions, but has not been implemented for students at high schools and other lower levels of learning. For this reason, my plan will include approximately 100 students of high schools, taking physics and learning in a virtual environment. I will also stick to specific topics in this interactive 3D learning environment, including Laws of Motion and Kinematics, which are often very technical in nature and require a special way of delivery that is readily provided by GBL environments.

How do emotions come into effect in my plan, though? Well, PlayPhysics involves role-playing and turn-taking in which students are required to achieve a particular mission. That mission is to save Captain Foster who has been trapped in a station in open space known as Athena. Participating students have to launch a spaceship from the earth and then participate at different levels to propel the spaceship. The challenge, which invites emotional response, is the calculation that students have to make so as to ensure that the spaceship reaches its target station on Mars or Jupiter, while ensuring this has been accomplished while the fuel tank is not yet exhausted.

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Evaluation and Evidence Plan

A typical Graphical User Interface (GUI) looks like this:

As can be seen from the above, an emotional model is already provided and a reminder on reporting emotions at the end of the game is readily available as shown in the following extractions from the above GUI:

So, what I will do is to engage students in this learning environment for a week, is make sure that each session of the game is preceded and succeeded by similar or related tests on the discipline or topic of discipline under examination. By doing this, I will collect data and call for assistance from professionals to use it and apply Pearson correlations to them so as to come up with dynamic sequences of Bayesian Networks of retrospective-learning, prospective-learning and activity. From these calculations and data, it will be possible to estimate the accuracy of the model of students’ emotions outlined in this draft of learning objectives. This will also depend on how randomly the results compare to the total size of the sample. Below is a sample of the student’s emotion model that had been obtained in a similar project using PlayPhysics by Munoz et al. (2016):

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Challenges So Far and Next Steps

The most challenging task in achieving this learning objective will be getting resources to conduct the research, which will require computational resources as well as professional support. While I may readily find a higher learning institution that has installed and implemented GBL environments, getting a high school which implements PlayPhysics might not be easy. Similarly, after collecting the much-needed data, it may take considerable financial resources to get professionals to do the required computation on the data, establish results that I require to ascertain the level of accuracy of my model and, indeed, my learning objective for this course.

But the challenges connected to this project will not be limited to issues of resources mentioned above, The other big challenge, which may change everything, is students’ response to the task. Will they be ready and willing enough to report their emotions at the end of each game session, or will some be overwhelmed and fail to give this indicative report? This is an important risk factor which I will need to address first.

Addressing all these challenges may not be possible at the moment. However, it is possible to draft a plan to avert detrimental students’ responses to the task. This will take the dimension of preparing students psychologically for the sessions and working each subsequent time to ensure improving positivity for the game sessions. This will require an introductory approach which explains all about the environment and learning objectives a student is expected to start participating in the project with. Then, students will be encouraged to report their emotions honestly in order to help improve the game constructs for them.

It is necessary to recognize that this learning environment and its implementation borrow from cognitive learning theories addressed by Munoz et al. (2013). Their discoveries are the major building blocks for the philosophy of educational technology presented in this personal draft learning objective. Therefore, a solution to students’ responses to the implementation of students’ emotional model will rely on a psychological approach, just as the analysis of data will.

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Finally, I will rely on outside fundings to ensure that I get to implement the model herein. This will require me to apply through an institution from which I expect to have a voice and an advantage of being trusted with financial support to implement my model. After that I will prove my hypothesis and contribute to the larger human knowledge and philosophy of educational technology. Similarly, my learning objective answers various questions related to the foundations of my beliefs in this kind of model, how this model will translate to effective learning strategies that take advantage of cognitive theory approaches, and how the instructions and assessments can be achieved in a classroom environment.

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