Supporting Deep Conceptual Learning With Technology

Technology can help educators train students' focus away from rote memorization toward deep conceptual learning by building on prior knowledge and making connections between concepts.

• By Peter Rillero and Helen Padgett
• 01/15/13

An example of discovery learning, the game WolfQuest lets players take on the role of a wolf in Yellowstone Park, where they explore the wilderness, hunt elk, and attempt to find a mate.

The Common Core State Standards' changes in math and science instruction are not just about content. The new standards ask learners to, among other things, demonstrate deep conceptual understanding of core concepts by applying them to new situations, as well as writing and speaking about their understanding.

This is easier said than taught, especially if the tools for teaching deeper conceptual learning are limited to traditional textbooks and lab materials. We join other researchers in concluding that one of the most effective ways to facilitate these profound changes in teaching and learning is through technology. Not only do virtual science and mathematics experiences allow learners to partake in more activities in less time and space, they also provide learners with complex and rich experiences that can lead to deep and lasting understanding of math and science concepts, as well as profound changes in themselves as learners.

Learners vs. Students
Deep conceptual learning is a distinct learning approach from surface learning, which is characterized by memorization, rote learning, and unquestioning acceptance of textual information. In deep conceptual learning, learners take what they know--aka prior knowledge--and deepen their understanding of the concepts. Some authors call people who seek deep conceptual learning "learners" and those who skim the surface "students."

The role of prior knowledge is important to deep conceptual learning, as it may support or hinder learning new material. Well-sequenced learning experiences ensure that learners connect new concepts with previously (and correctly) learned material and deepen their learning. However, when misconceptions exist, learning can be slower because learners don't necessarily always reject prior knowledge and accept new instruction. They rather tend to gradually refine and transform prior knowledge to accommodate new scientific ideas. Again, well-designed experiences in supportive environments help learners develop deeper and more accurate conceptions in the face of inaccurate prior knowledge. 

While different people may naturally gravitate toward one type of learning, the context in which the learning takes place will have an impact on how the learner responds. For example, time pressures and cramming for exams lead to surface learning, as do assessments that focus only on superficial details. On the other hand, learning environments with rich resources, warm classroom cultures, appropriate workload, and well-sequenced curriculum can promote curiosity about a subject and lead to deep conceptual learning. As might be expected, research suggests that deep learners have better retention of information and apply it better than surface students do.

The demands of deep conceptual learning mark a commensurate shift in teaching. Just asking students to learn deeply is not enough. Teachers will need help in bringing about this paradigm shift, which involves several different methods--called deep conceptual learning models or DCLM--to teach deep conceptual learning.

Beyond learning new pedagogical models, however, teachers and their students need access to appropriate technological tools. Technology-enhanced learning experiences allow learners to explore concepts that otherwise couldn't be presented in class because of safety concerns or a lack of equipment, materials, or lab space. Web-based systems are easily scalable from dozens to thousands of students school- or district wide. Online activities can engage digital-age learners in core concepts using real-world scenarios, compelling graphics, and an active learning pedagogy.

Here are few examples of technology-enriched deep conceptual learning methods that can help student students who learn superficially become deep conceptual learners.

Discovery Learning
Discovery learning creates experiences for learners to join concepts together. For learners to join concepts together, they need to think about the concepts. Discussions with other learners and teachers can induce thought.

Discovery learning can have a lasting impact because learners not only experience the content, they also improve their inquiry and critical thinking skills. Hands-on science and math manipulatives--both physical and digital--create fertile grounds for discovery learning. But virtual experiences allow for more experiences at the same time and also permit experiences that are too difficult, dangerous, or expensive to do in class.

Students can learn about ecology in a classroom, often in an uneventful, non-inspirational way. Consider, on the other hand, WolfQuest, where learners are immersed into a 3D experience as they become wolves in Yellowstone Park and directly discover strategies for survival. With their realistic wolf avatar they hunt elk, look for mates, and mark territory with raised-leg urination. The discoveries they make about the wolves make them want to learn more. Virtual discovery learning allows learners to do things that are not possible in a typical classroom and to engage in more discovery learning experiences in less time.

Multiple Representations
Multiple representations can provide unique benefits when students are learning complex new ideas, especially in mathematics. Ainsworth's research on learning with representations has shown that when learners interact with an appropriate representation their performance is enhanced. The multiple representations could include graphs, tables, or written explanations that may help learners to visualize the concepts being presented.

The term "representation" refers both to process and to product. A learner who draws pictures of trucks to determine the total number of trucks he has when he combines 12 trucks and five trucks is using the picture of trucks both to find and represent the answer.

Using multiple representations also presents the opportunity for multiple entry points to help teach concepts, because each point allows learners to arrive at their understanding in more than one way.

Examining learners' representations gives teachers valuable insight into their thinking, illuminating how students solve problems, comprehend mathematical ideas, and model mathematical solutions. The internet offers powerful ways of delivering multiple representations , such as the lessons on the National Council of Teachers of Mathematics' Illuminations website. Learners can develop important 21st century skills as they model mathematics and construct viable arguments. For example, in "Exploring Linear Data," learners model linear data in a variety of settings that range from car repair costs to sports to medicine. They can work to construct scatterplots, interpret data points and trends, and investigate the notion of line of best fit.

Deep Analogies
Analogies are effective techniques to help learners connect new concepts to concepts already mastered. But just as there is superficial and deep learning, there are superficial analogies--comparisons that are stated but never fully explored--and deep analogies, which involve exploration.

Deep analogies consider how the target concept is similar to the analogy and, since all analogies are imperfect, explore where the analogy breaks down. Deep analogies help learners to think in rich ways about concepts and to join concepts to existing knowledge. Since scientists use analogies for scientific reasoning, discovery, and communicating, exploring analogies also helps learners develop these abilities. 

Virtual resources provide excellent opportunities for students to develop an understanding of deep versus superficial analogies. As an example, "The Human Eye" is a well-produced video with a weak use of analogy. The video starts off by mentioning that the eye is similar to a camera but then only describes the structures and functions of eye parts without exploring the analogy.

By contrast, "The Anatomy of the Eye" and "The Differences Between Your Eyes and Your Camera" take the analogy deeper by investigating the similarities between the eye and camera, such as exploring how the lenses in each work. Moreover, these two videos also explore where the analogy breaks down, which helps to deepen learning and make learners thirst for more information.

Challenge-Based Learning
Mathematics and science teachers must teach students not only to solve problems, but also to learn content through problem solving. Challenge-based learning is a multi-disciplinary approach to education that encourages students to leverage the technology they use in their daily lives to solve real- world problems. By giving students the opportunity to focus on a challenge of global significance and apply themselves to developing local solutions, CBL creates a space where students can direct their own research and think critically about how to apply what they learn.

The result, as evidenced by research conducted by The New Media Consortium, is increased engagement, extra time spent working on the challenge, creative application of technology, and more student satisfaction with schoolwork. Students mastered the subject-area content and their engagement with the material and with learning improved.

In challenge-based learning, as in problem-based learning, the teacher's primary role shifts from dispensing information to guiding students' construction of knowledge around a problem of global importance. Learners refine the problem, develop research questions, investigate the topic using a wide variety of primary source material, and work out a variety of possible solutions before identifying the most reasonable one. Learners document their process and produce high-quality, text-based or interactive reports of their findings, all of which further give the process relevance to the world of actual work. It is crucial that the challenge actually relates to the real world and for it to have an impact on the students' families, local communities, or school.

The "Challenge Based Learning" website offers a range of projects that will help students develop a deeper knowledge of mathematics while entering into a global discussion about real-world issues. A newly reorganized support resource section within the CBL community is called the Toolkit, where visitors can find--and contribute to--a searchable database of resources available for supporting all facets of challenge-based learning.

Conclusions
Deep conceptual learning is an important goal in education. It moves beyond rote memorization for a test and stresses learning by leveraging interests and making connections between concepts and real-world situations. It is consistent with the Common Core standards in mathematics and the framework for science. Discovery learning, multiple representations, analogies, and challenge-based learning are methods for helping students move from memorization to become deep learners.