In this section, we're going to look at traits and states among learners in terms of learner analysis. In the previous section, we talked about similarities and differences among learners, and this section, we will add some temporal element in terms of to what extent some characteristics will stay stable over time or otherwise. This is the illustration for the Addie model. We are still in the first stage, the analysis. Very quick recap. Why are we doing learner analysis? To know who our learners are, how they prefer to learn. To scope the intended learning task and the learning environments for individual instructional units. To know where your learners are in reference to the intended learning objectives or learning goals. Finally, to scope the overall instructional design effort for the entire curriculum that's beyond individual instructional units. So, the emphasis to begin with would be looking at the difference among learners cognitive styles, their learning styles and their learning strategy. Cognitive styles is usually a stable trait that deals with individual knowledge acquisition and information processing. Learning style could be a trait or a state, the debate is still ongoing. Nevertheless, learning style is focused on how learners prefer to interact with learning environment cognitively, emotionally, physically, and socially. Learning strategies are approaches learners consciously choose to apply in order to achieve learning objectives. Those choices are based on learner's cognitive styles, how they are used to interact with information and also based on their learning style how they have been experiencing learning processes fast far. Hopefully, they're going to choose appropriate learning strategies in order to complete the intended learning tasks. Let's look at cognitive styles. It's individual differences. The way I process information will be very different from the way you process information. This is relatively stable based on our schooling experience, based on our social experiences. The cognitive styles, we develop them into a stable trait if you will. Our cognitive style will influence our attitude, value, and social interactions which is different from learning preferences and learning strategies as we discussed earlier. It's useful for instructional designers to understand cognitive styles which will provide insight into not only whether individual is likely to be able to learn, to complete a particular learning task, but also why they choose to do so and otherwise. One example of cognitive style will be looking at learners according to two dimensions. First one is the Wholist-Analytical dimension. It's the habitual way in which an individual processes and organizes information, a global view of information versus component parts. So, basically, this dimension will tell us whether or not the learners will pay attention to the big picture first or to the detail of the information that is presented. The second dimension is the verbal and imagery dimension. So, this dimension will tell us whether or not our learners are more likely to interact with pictures or texts or combination of the two. The second example of cognitive style is broader. We also consider that as potentially learners thinking style. This's called the Gregorc Style Delineator. There are four distinctive and observable styles: Abstract, Concrete Random, and Sequential tendencies. Those are four constructs if you will. As a result, we will have four quadrants. Concrete-Sequential, Concrete-Random, Abstract-Random, and Abstract-Sequential. The Gregorc Style Delianeator will tell us learners' accumulated predispositions, but individuals need to be able to function outside of their natural style. That's important in order to accommodate different learning environments. The first dimension of the Gregorc Style Delineator will be abstract versus concrete. The abstract perception tells us learner's ability to think in an abstract sense based on their intuition or imagination. The concrete perception is the quality demonstrated by learners in terms of to what extent they will prefer concrete, tangible representation of information and activities. Sequential versus random. Sequential person deals with data in a linear organized manner. They tend to plan things out step-by-step, very structured. Somewhat predictable. A random person prefers to deal with information in chunks, skipping steps whenever possible, less predictable and less likely to carry out linear thinking processes. So, if you combine those two dimensions, you have the following four combinations of cognitive styles. Concrete-Sequential, we will see those learners will be practical and well organized. So, we can follow this guideline to initially design our learning environment. Concrete-Random, practical and desire options, that's the randomness part of this particular category. Abstract and Sequential, abstract concepts, biologically sound. Scientific topics for instance will fall into this category. Abstract-Random, we will see learners fall into that construct will be highly constructivist. If you recall earlier we talked about learning theories. When it comes to constructivist learning, it's important to provide a rich learning environment for learners to develop the meaning of the knowledge. In-video question. Should we consider learning style a trait, a relatively stable over time and context, or a state, dependent of time, space, contexts, and tasks? The debate in terms of trait or state when it comes through learning styles is still ongoing. If you follow the research literature, it's an interesting topic within the field of instructional science, as well as instructional design. So, at the core of the learning if you will, the core of the learner will be grounded in their cognitive styles. So, that branch out to the way they process information; tangible behaviors, observable choices. That branch out to instructional preferences dealing with different types of instructional cues, cognitive cue, emotional cues, social cues and so forth. Based on the cues, then the learners will choose learning strategies, of course, instructional designers who will provide options for learners to choose from. Therefore, ideally, then those learning strategies will lead to successful interactions between learners and the learning environment. So, this hopefully, will give you some ideas in terms of what are the relatively stable aspect of the learner characteristics when comes to cognitive styles, learning styles, and instructional strategies. Some are changing over time, some stay relatively stable over time. It's important for us to understand this difference because as the instruction moves forward, whether it's a short-term instruction or long-term instructional program, the influence of time is always important. So here the influence of time deals with the changing learner characteristics to some extent. Beyond that, we can also see the influence of time that might impact learner's engagement with the learning environments. It is more appropriate considering the ongoing debate of trait or state when it comes to learning style. We would like to consider learning styles as a preference, learners' preferences to choose how they interact with the learning environments by themselves. Nevertheless, learning styles are different from cognitive styles. Learner styles are able to help us differentiate learners within the group, but it shouldn't be the only criterion we use to put students in different groups. We can also see learning style, if you consider as a preference, the preference had been reinforced by learners' prior experiences. So, therefore, again, prior learning is important as part of the learner analysis outcome. The very last item to emphasize that again learning style, it could be the combination of traits and states, that are not necessarily mutually exclusive. Now, let's look at activities we can carry out in order to analyze learner characteristics. We can use interview or we can survey the learners within the target population. Ideally, we would like to get data from all potential learners, but oftentimes, logistically that is just not feasible. So, we can sample participants from the target learner population. We can also observe how they behave, how they work in the realistic learning and performance settings. So, observation from us, how they interact with peers, how they apply skills and how they solve problems for instance. We can also use published archive information about the population, it's more generic, but it's still useful. Finally, we have the records, documents created by other learners in their target population. We can also use learners' work examples to assess their skill level, knowledge level, ability level as part of the learner analysis process. Implication-wise for instruction design, the value of the learner analysis could be realized in this list of instructional design variables if you will. First is the pace of the lesson, so that deals with learners' cognitive abilities in terms of processing information. Number of practice activities. You can make that decision based on your learners' cognitive styles where they prefer more concrete type of learning experience or where they prefer more abstract type of learning activities. Based on our understanding of learner's prior experience, we can establish the relevance of the content. Ideally then, this will lead to better motivational support from the instruction. Techniques for gaining and focusing attention depending on learner's preference, how they prefer to deal with information, deal with activities. Examples and practice activities, again, could be relevant to the concreteness of the experience or the abstract imaginations prefer by the learner audience. Amount of structure and organization, you will find out whether or not your learners are more likely to follow step-by-step procedures or are they more interested in in a constructivist way of approaching learning? Types of feedback to provide, this will be relevant, will be based on learner's prior experience, usually for novice learners we provide more detailed feedback, more scaffolding, for learners with more experience or some level of expertise in the area, we can somehow condense the feedback since not too much explanatory information might be needed. Learner control to what extent learners will prefer, will choose, will perform well in a more autonomous learning environment, they can choose when to begin, when to end their learning, they can manage the pace of their own learning. Now, our learners are ready for those type of control. However, then there's reading, vocabulary level in their native language or in a foreign language or somewhere in between a combination of multiple languages within the instruction. Amount and types of reinforcement. This deals with the conditions for learners are used to be participate. Amount of time allowed for instruction and remediation. So this could be based on learner's prior educational level, their prior experiences about the topic and also the logistics of the instruction available. The amount and type of learning guidance, this is somewhat different from the feedback aspect of the instructional design. You can consider that as part of the structure within the instruction. Again, this will come from learners prior experiences on a topic and their prior experiences in receiving similar instructions before. Level of concreteness or abstraction, this will have implication regarding the design of instruction activities in particular. More hands on approach or more reading, more discussion type of instruction activities are preferred. So, this is just a short list of potential instructional design variables that we can consider based on the information from learner analysis. Reality check on learner analysis, the process itself can be time and resource consuming. Logistics become a limiting factor in many cases for instructional designers to carry out a comprehensive learner analysis. By referring to data collected earlier can save some time and resource in terms of conducting learner analysis and I might give you additional allowance to focusing on other aspects of a learner analysis. Learning styles is well adopted by the trait versus state debate remains ongoing. The best way for instructional designers to approach this would be combining the two in order to cover all aspects of the learning style and its implications to initialize your design. We should not assume all learners are the same, and hopefully, learner analysis would support our position. Diversity among learners is strength and for enriched learning experiences. If you can recall, the design of constructive zone environment for instance would be benefit tremendously by embracing the diversity among our learners.
