Small Changes for Big Learning Improvements

If we want to help students build richer conceptual networks, we must begin by surfacing their prior knowledge in ways that reveal their confusions, mistakes, and emerging conceptual understanding.

When we demonstrate our expert knowledge through lectures and modeling, prior knowledge is neither surfaced nor activated, and we are robbed of the chance to see how students are organizing and crafting conceptual connections. Watching us work through problems lures them into a false sense of understanding. Because we act with expert fluency, they perceive the task as simpler than it really is. So how can we successfully activate students’ prior knowledge so that their understanding can change and grow?  

Lang offers a strategy called What do you already know? to “solicit and address existing knowledge networks” (p. 101). Let’s see how this strategy might work in an Informatics class where the teacher wants to know how students approach the central disciplinary process of sequencing code.

Example: The teacher gives the students five possible sequences for a line of code. Two of these sequences work, two of them reflect typical novice mistakes that are important to address, and one of them can only work under specific conditions. Each option thus represents a different way that students may have organized some key principles at this early stage of their learning. Students first work on their own to choose which sequence is best, then they compare their answers with those of other students in a small group, and finally the groups come to consensus and share their answers. After the groups share their answers, the teacher gives them feedback on their naïve attempts.

This approach ensures that the teacher gets a clear picture of students’ prior knowledge and how they are using it in the early stages of their learning about coding. It also prepares the students to receive and integrate newer, more expert ways of thinking about coding into their current understanding.

In addition to integrating more expert ways of thinking, students also need to develop a network of conceptual connections that helps them make sense of our disciplines.

One strategy to help them articulate these connections is the Concept Map, which usually involves asking students to create a visual representation of their conceptual connections within or between the big ideas or principles of a discipline.

Lang warns us that concept maps are often misused because teachers ask for a simplistic map of novices’ concepts. For example, asking students in a policy course to create a concept map of their current understanding of a policy analysis framework may result in students recreating a chart they remember from the textbook.

A more effective way to require students to explore and develop their conceptual connections is to have them create more focused maps as a response to a meaningful disciplinary question. Let’s see how this strategy might work in a Social Policy course.

Example: The teacher asks students to read about a policy on urban poverty and then respond to this prompt: “Draw a concept map that shows which key concept or concepts from the policy analysis framework would be the central focus in a critique of this policy and which concept or concepts would be ancillary. Be prepared to explain and defend how you are prioritizing specific concepts.”

After students have created and justified the organization of their ideas represented in the concept maps, the teacher gives them a quite different policy on urban poverty and asks them to create a different concept map so that they begin to see how the concepts in the framework can be re-prioritized depending on contextual variables surrounding the policy.  

Another strategy for making thematic or conceptual connections is the Minute Thesis, an “ideal small teaching activity: free, easy, and capable of use in any size class, for any length of time you wish, from 10 minutes to the full class period” (p. 106). Let’s see how Lang uses the minute thesis in his Literature course. 

Example: Lang writes the titles of the novels the students have read in one column on the board; in a second column he writes the themes that they have seen so far in the semester.

A student is asked to go to the board, circle a theme, and then draw lines connecting that theme to two novels. But the real work comes next when students are given one minute to come up with a thesis for an argument that explains how the two novels are connected to that theme.

Students share their ideas with the class and when enough new connecting arguments have been made, a new student comes to the board and draws her connections.

Lang tells us that not only do students do the deep thinking practice of making and explaining connections, but also they “gain some practice in what might seem to them the mysterious process of coming up with new or original ideas” (p. 108).

The minute thesis is easily adaptable to any discipline: one column on the board can be homework problems and the other column can be core principles or concepts. In a course like Physical Chemistry, one column could contain key concepts such as the three laws of thermodynamics, entropy, equilibria, and so on; the other column could contain five diagrams of real-world objects whose behavior can be explained using the key concepts in the first column.

While students may initially be tentative about explaining the connections between concepts and phenomena in any field of study, requiring them to practice this expert habit of mind helps them forge and build upon these connections for future use.  

In his chapter “Self-explaining,” Lang introduces us to a powerful teaching strategy that can help us push students to guide their own learning. Self-explaining means requiring students to step back from the disciplinary work they are doing and explain their thinking to themselves (or to you), either out loud or in writing. There is some intriguing research that supports this approach. 

Chiu and Chi (2014) found that students who were able to solve Physics problem successfully did much more “self-explaining” than unsuccessful students. The more successful students mindfully explained to themselves the inferences they were making as they solved problems, drew on Physics principles as they made these explanations, monitored their comprehension, and paraphrased problems and principles in their own words. In other words, these students used self-explaining to create a richer set of connections between problems, readings, principles, and their emerging understanding.  

This kind of self-explaining is essential to developing the mental connections that support deeper thinking, and Lang offers a manageable strategy to prompt students to self-explain: the Why are you doing that? strategy.

We can use this strategy in class by circulating through the class while students are working and asking them questions like

• “Why are you doing that?”
• “What reason is guiding your choice?”
• “What principle are you using?”

The goal is to require students to identify the mental work they are doing or need to do and articulate their thinking about that work. As students describe the choices they are making, they can examine their thinking to see if it is being guided by core concepts - or they may realize that their thinking is not well connected to core concepts. Self-explanations can provide effective feedback to support student thinking because we (and they) can now “see” that thinking.

This small teaching strategy can also be used when students are working on their own outside of class. Before they turn in drafts of projects or papers, we might require them to annotate a few pages, slides, or tables and explain what principles or strategies they used to guide their work.

As students explain their thinking, they recognize how they are or are not using the big themes, principles, or practices of the discipline. Self-explaining through annotations deepens students’ thinking by pushing them to connect their work to the core of our courses and our disciplines.