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Personalized E-Instruction of Manual Exposure of DSLR Camera  

Problem

Many amateur photographers find using manual setting of exposure of DSLR cameras is challenging. Although there are tons of e-instructions of the manual exposure of DSLR camera, most of them are synchronous, linear lessons that are not adaptive to the learners' differences, such as their prior knowledge, personal goals and strategic behaviors. The leaners would easily drop out if the learning experience is either too easy or too hard.  

Solution

This individualized e-instruction designs and prototypes a adapting instruction that is adaptive to the demands of the domain, learner characteristics, and the learner’s path in the ongoing learning activity. "To be adaptive" in this project is defined as (Aleven et al., 2016):  

 

"A learning environment is adaptive to the degree that (a) its design is based on data about common learner challenges in the target subject matter, (b) its pedagogical decision making changes based on psychological measures of individual learners, and (c) it interactively responds to learner actions (cf. Aleven et al., 2015; Aleven, Beal, & Graesser, 2013). "

 

The focus of this prototype is the adaptive learning experience in the intelligent tutoring systems not the adaptivity in learning technologies.

The learning objectives for the leaners of this E-Instruction are:

 

  • Understand the three key elements of the photography exposure: aperture, shutter speed, ISO, and their relationship. ​

 

  • Be able to adjust the three parameters according to achieve goals within preferred contexts.  

 

 

Citation: Aleven, V., McLaughlin, E. A., Glenn, R. A., & Koedinger, K. R. Instruction based on adaptive learning technologies. Handbook of research on learning and instruction. Routledge

How it works

Before the learners starts to take the E-lesson, they are required to take a pre-test that is created based on the cognitive task analysis. The system will choose learning paths for the learners accordingly based on their performances in the pretest. The learning path and learning objectives will be visible and explained right after the learners take the pre-test. During the E-lesson, the learners will have the choice of what type of learning contexts they prefer. After they finish all the tasks, they will take post-test. At the end, the learners will get the personalized learning reports to help them understand their learning behavior and outcome. The following screen shots illustrate some primary learning experience.  

The contextualized pre-test tasks are created based on the cognitive task analysis, which helps to identify the prior knowledge and detect the knowledge deficiency.

The screenshot of one of the pre-test tasks

The pre-test report informs the learners their current knowledge level of the subject and draw their attention of their learning focus. 

The screenshot of the pre-test report

The worked example is provided to demonstrate how to solve the problem in the context.

 

If the learner can review the basic concepts and rules by clicking the shaded texts sparsely distributed through the lesson. All the basic concepts and rules in this e-lesson have been highlighted to provide learners with hypermedia environment.

The screenshot of the worked example with hyperlinks of the basic concepts  

The system offers the learners different learning contexts. For example, if the learner clicks the button of “Nature”, nine categories of scenarios on Nature will be presented as below. The rationale for this feature is that the user interviews shows many learners want to practice the exposure settings in specific areas. The learner who loves portrait photography feels bored when learn the exposure setting in the context of the landscaping. 

The screenshots that shows how the learning contexts can be adaptive to the learners' interests 

The E-Learning principles applied in this E-lesson are: Fading worked example, Self-explanation and Explanatory feedback.

 

As the learners gain more expertise, the "expertise reversal effect" may appear. Fading worked example fades out the steps gradually until they can solve the task entirely on their own.

 

Self-explanation prompts are added to the multiple choices worked example task to require the learner to think about the rationale behind their choices. 

Explanatory feedback provides a much better opportunity for learning because it incorporates an explanation not just tells the learners the answer is wrong. 

The screenshots of the instructions that incorporate the E-learning principles, which haven been proved effective by research.

The leaners will get the personalized learning report to help them monitor their learning goals achievement progress, time duration they spend to learn,  their error rates along the tasks and their error types and frequency. 

The screenshots of the learning report

Reflection

structured , ill structured ? how to adapt to the differences and also the simolarities ? 

The adaptive learning experience in the intelligent tutoring systems