Instructional Explanations as a Classroom Teaching Strategy

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abstract

Instructional explanations are teacher’s deliberate contribution to learning to correct, coherent, and complete answers to students’ queries. In the first part of this paper, theoretical background and confusing concepts of instructional explanations will be reviewed focusing on verbal explanations. In the second part, empirical studies on effectiveness of instructional explanations will be examined. Lastly, in the third part, various empirical studies will be discussed to come up with strategies and considerations for improving instructional explanations. These studies and suggestions will be examined in terms of the two facets of instructional explanations: design and delivery.

Key words: instructional explanation, learner impasse, mental model, mental passivity

Introduction

Great teachers have existed before technology was adopted in classrooms, before the idea of instructional design was advocated, and even before the school existed. Some teachers are admired because of their noble character, and others are admired because of their enthusiasm to classroom teaching. Particularly, some teachers provide such rich explanations for a difficult content that any student can understand easily and concentrate on a task, while others provide just simple and poor explanations, unfortunately. What makes this difference? This study begins with this basic question.

The topics of this study are not new at all, and research papers have proliferated from the 1980s (Leinhardt & Steele, 2005). The topic, ‘great teachers’ or ‘effective teachers’ have been discussed among the scholars of teacher education, and ‘good instructional explanation’ was a sub-topic of ‘effective teachers’. Also, ‘pedagogical content knowledge’ is an essential component of instructional explanation (Ball, Thames, & Phelps, 2008; Shulman, 1986; Sullivan, 2008). An effective teacher is not just a charismatic and silver-tongued teacher. The teacher must be an expert in the subject content. Recently, some researchers view instructional explanations in combination with learners’ cognitive process (i.e., Maclellan, 2015; Sánchez, García-Rodicio, & Acuña, 2009), and others investigate the nature of instructional explanations in computer-based learning environments (i.e., Berthold & Renkl, 2010; Roelle, Berthold, & Renkl, 2014).

My viewpoint on instructional explanations is that they are the outcomes of teachers’ deliberate preparation for the classroom teaching. The ‘preparation’ implies instructional design. Thus, ‘good preparation’ requires instructional design theories as well as rich pedagogical content knowledge. In addition, instructional explanations are a form of classroom delivery. Effective teachers deliver the learning content such an effective way that most learners feel the content is very easy to understand.

The focus of this paper is instructional explanations as a classroom teaching strategy. What are the background and main theories regarding instructional explanations? How are the instructional explanations different from instructional design, disciplinary explanations, and classroom management? How effective are instructional explanations in various instructional settings? What kind of strategies has been proposed and investigated to improve instructional explanations? What considerations and cautions have been suggested for successful implementation of instructional explanations? Those are main questions of this paper.

Theoretical Background

Gaea Leinhardt (2001, 2010)defines that the instructional explanation is teacher’s deliberate contribution to learning to correct, coherent, and complete answers to students’ queries. Instructional explanations can be categorized into three types: verbal, visual, and discussion (Geelan, 2012). Verbal explanations are presented in the form of lecture or demonstration of learning content. Verbal explanations can be accompanied with visual diagrams and demonstrations. Also, explanations can be collaboratively generated in a classroom discussion. This study will mainly focus on verbal and visual types of explanations because the researcher’s future dissertation will analyze online shared videos in which classroom discussions are very limited.

One of the good examples that analyzed verbal types of instructional explanations is David Treagust and Alan Harrison’s (2000) research. They analyzed Richard Feynman’s lectures. The book “Six Easy Pieces” (1994) is a collection of Feynman’s lectures between 1961 and 1963, and contains in-depth explanations for the general public on physics such as atom, energy, gravity, quantum physics, etc. Treagust and Harrison categorized Feynman’s explanations by (a) analogies and metaphors, (b) axioms, (c) anthropomorphic and teleological statements, (d) concepts and examples, and (e) imagination and rotational reason. Dagher and Cossman (1992) analyzed junior high school science teachers’ verbal explanations. They categorized and labeled them into 10 types: analogical, anthropomorphic, functional, genetic, mechanical, metaphysical, practical, rational, tautological, and teleological.

Wittwer and Renkl (2008){Wittwer, 2008 #29}{Wittwer, 2008 #29} reviewed various empirical studies and proposed four general guidelines for designing instructional explanations: instructional explanations should (1) be adapted to the learner’s knowledge prerequisites, (2) focus on concepts and principles, (3) be integrated into the learner’s ongoing cognitive activities, and (4) not replace learners’ knowledge-construction activities. In sum, Wittwer and Renkl suggested that instructional explanations should be tailored considering an individual learner’s prior knowledge, and instructors should develop approaches to understand learners’ understanding levels.

As was mentioned in Wittwer and Renkl’s (2008) guidelines, it was argued that instructional explanations alone are not effective and they should be examined in combination with learners and learning environments. In particular, constructivist perspectives emphasized on student learning (Jonassen, 1999), and this trend shifted researchers’ attention away from teacher’s activities (Geelan, 2012). However, the research on instructional explanations does not exclude student learning. Rather, this is a different approach to exploring effective ways of learning. Moreover, it is a practical way because improving teacher’s performance appears a quicker and easier approach than improving learner behaviors and learning environments.

Similar but Different Topics

Instructional explanations have two facets: design and delivery. We will discuss in detail about this later. In a nutshell, effective teachers prepare and rehearse a lecture beforehand, then deliver the content very effectively like a great actor.

Instructional Design and Instructional Explanations

Instructional design can be defined in a broad viewpoint or a narrow viewpoint. In a broad viewpoint, instructional design is defined as “a systematic process that is employed to develop education and training programs in a consistent and reliable fashion” (Reiser & Dempsey, 2007, p. 11). According to this definition, instructional design is similar to instructional systems development (ISD). ISD covers all the systemic and systematic process of producing a training as the ADDIE – one of the most popular ISD models illustrates, whereas instructional explanations focus on teacher’s activities before and during a classroom lecture.

In a narrow viewpoint, instructional design theories mainly focus on task and learner analysis and content design (Reigeluth, 2013). For example, Reigeluth’s (1999) Elaboration Theory suggests providing learning content from simple to complex, and general to detail. Merrill’s (1983) Component Display Theory helps designers to analyze and display learning content in two dimensions: type of content and performance.

The first difference is that Instructional design theories are great tools for one of the two facets of instructional explanations: design. However, delivery is another realm like a good script writer is not necessarily a good actor. Second, instructional design theories prescribe whichever methods that are deemed to be effective for the specific learning situation such as discussion, group project, and/or problem-solving as well as lecture. Instructional explanations are mainly in the form of a lecture in a classroom. Research on instructional explanations does not argue that other methods are inferior but it just focuses on how to best implement instructional explanations.

Disciplinary Explanations and Instructional Explanations

Instructional explanations are different from disciplinary explanations (Geelan, 2012; D. Treagust & Harrison, 1999). For instance, Treagust and Harrison (1999) compared science explanation and science teaching explanation. Science explanations are strictly theory and evidence-driven, and described in correct scientific terminology. However, Science teaching explanations are less rigorous, and often use rich and creative metaphors, analogies and models. Science teaching explanations are uniquely created by teacher’s pedagogical content knowledge, and stimulate student mental models so that they can construct the content and process. In other words, the difference can be analogized to a distinction between explanation and understanding. Strasser (1985) identified explanation as the ‘natural science’ and understanding as the ‘human science’. Whereas science explanation is in the realm of natural science, science teaching explanation pursues human understanding.

Classroom Management and Instructional Explanations

Usually, new teachers and student teachers are concerned about classroom management. Even though a teacher has a great lesson plan, no one can effectively teach if the class is not reasonably ready to learn. Therefore, it is argued that all the teachers need to learn about classroom management strategies first (Berliner, 1988; Evertson & Weinstein, 2013).

However, other researchers (Emmer & Stough, 2001; Shulman, 1992) argue that if an effective teacher presents something compelling and interesting for students to learn, then classroom management will not necessary because of students’ intrinsic motivation and curiosity. Most of all, one of the top guidelines of classroom management strategies is to make learning engaging because if a teacher does not have well-designed content and not deliver it effectively, no classroom management strategies will work (Simonsen, Fairbanks, Briesch, Myers, & Sugai, 2008).

Effectiveness of Instructional Explanations

Early studies on instructional explanations attempted to compare the effects of different types of instructional explanations. For instance, in VanLehn, Siler, Murray, Yamauchi, and Baggett (2003) study, forty-two students participated in sessions with two expert tutors on the subject of physics. The tutoring sessions mainly consisted of lectures although the tutors were very experienced and well prepared. During the lecture, types of explanations were coded by researchers. After the posttests, the results showed that learning gains were not correlated with any of the explanatory codes. It means that different types of instructional explanations do not make difference in learning outcomes. Similarly, in the research of Chi, Siler, Jeong, Yamauchi, and Hausmann (2001), a passage regarding heart functioning was presented, and eleven students and tutors were asked to maintain a dialogue about it. After the dialogue session, the students solved a set of questions involving both shallow and deep learning. The researchers found that there was no correlation between tutorial explanations and deep learning. Furthermore, learning was not impaired when tutorial explanations were removed. This implies that students’ learning outcomes do not differ from tutor-generated explanations but from a different process.

More studies have been conducted to find effects of different types of instructional explanations. It has long been debated whether only one and the best solution should be presented for a mathematical problem or multiple solutions are better for learners.  Große and Renkl (2006) tested the effectiveness of presenting more than one solution methods for mathematical problems. In their 2 x 3 factorial design, multiple solution methods and uniform solution method were compared in three different settings of instructional support (none, self-explanations, and instructional explanations). The results showed that multiple solution methods were superior in all three conditions, and no interaction effect was observed. Meanwhile, Schworm and Renkl (2006) showed instructional explanations can even be undesirable for certain learners. They compared the effectiveness of self-explanations and instructional explanations for mathematics student teachers. The results showed that self-explanation prompts had favorable effects on learning outcomes. Yet, instructional explanations decreased the student teachers’ self-explanation activities and also their learning outcomes. Interestingly, the student teachers ‘subjectively’ perceived that they best learned with instructional explanations, whereas the learning outcome was measured ‘objectively’ higher in self-explanation mode. The researchers concluded that instructional explanations reduced the learners’ efforts in generating explanations, and this hampered learning outcomes. In conclusion, instructional explanations could be ineffective for certain populations such as half-experts (student teachers), and in a certain task such as constructing explanations for their future teaching.

It is not surprising that instructional explanations alone are not always effective. That is why traditional lecture-style instruction has been criticized, and learner participation and knowledge construction have been emphasized. More recent studies tried to explore instructional explanations in consideration with learners.

Inoue (2009) observed and analyzed thirty-four novice teachers’ rehearsals. It is obvious that every instructor prepares for a class by designing instruction, developing learning materials, and/or practicing instructional explanations. However, it is not an easy task for a novice teacher to give conceptually rich and meaningful explanations. One way to improve novice teachers’ pedagogical content knowledge (PCK) and the quality of their explanations is to rehearse and fine-tune their instructional explanations like actors or musicians rehearse before performing in front of audiences.

In the research by Inoue (2009), interesting observation results are (a) “Most of the presenters failed to consider possible confusions and misconceptions that elementary school students may have (p. 51),” (b) “Most of them failed to take advantage of various essential educational opportunities that emerged in their presentations for discussing important assumptions that underlie the representations and rationale that they used (p. 51),” and (c) “It was impossible to describe a linear, simple formula for the ways their PCK interacted and influenced weaknesses of the explanations at the deep level. (…) the step-by-step deconstructions of their actions and utterances appeared to be the only way to give a meaningful valuation of the explanations (p. 51).”

This study implies that instructional explanations have two facets: design and delivery. One of the main activities, when a teacher prepares for an instruction, is instructional design. This is similar to writing a script of a theater play. Like a good play requires a good script, good instructional explanation requires a good instructional design. However, there is a big difference between actors’ acting and teachers’ delivery. Acting follows the script and focuses on dramatic expressions of the script, whereas teacher’s delivery keeps adding or omitting instructional components while interacting with learners. Effective teachers are good at fine-tuning and self-feedback process during the delivery. Stodolsky (1988) referred to this as “teacher’s reconfiguration of activity structures.”

The research by van de Pol and Elbers (2013) is a good example of the nature of teacher’s delivery. They analyzed 22 preservice teachers’ lessons in terms of teachers’ delivery and student learning. Regarding the teachers’ delivery, they focused on the ‘contingency’. The Contingency Shift Principle is (1) increase control by providing answers or explanations when students fail, and (2) decrease control by asking open questions when students succeed. The results showed that if students’ entry understanding level is low, contingent support was effective for student learning. More importantly, they found that teachers tended to overestimate students’ understanding. It means that the preservice teachers did not provide enough increased control even when students were not fully understanding the content. Like this, teachers usually have a hard time in deciding what to tell and not tell. They have to make decisions every moment by carefully sensing learners’ reactions.

Strategies and Considerations Proposed in Empirical Research

In the previous section, it was discussed that design and delivery are two main facets of instructional explanations. To improve the design aspect of instructional explanations, researchers suggested considering learners’ mental model. For the delivery aspect, researchers focused on the mental passivity of learners. With the aspect of these two topics, strategies and considerations for successful implementation of instructional explanations will be discussed in this section.

Learners’ Mental Model

In Calin-Jageman and Ratner’s (2005) study, two conditions were compared with a control group. In one condition, kindergarteners explained the expert’s answers (Explain-Expert), and in the other condition, children explained their own answers (Explain-Novice). The control group did not generate explanations (Control). Explain-Expert children showed better performance than the control group. The Explain-Expert group also learned the expert’s strategy more quickly and used it more frequently than the other groups. In sum, this study supports the importance of well-designed instructional explanations compared to self-explanations.

Interestingly, Explain-Novice group was not significantly superior to the Control group. We tend to assume that creativity is way better than replication. Calin-Jageman and Ratner’s (2005) study shows an example of ‘impasse’. When learners detect problems in their mental models but they cannot generate their own explanations to solve them, it is called learners face impasses that they cannot overcome (Sánchez et al., 2009).

Here is another example that learners are discouraged to utter self-explanations when they experience impasse. Kendeou and van den Broek (2007) prompted a group of college students to self-explain while reading a text about heart diseases. The researchers correlated different utterances with learning. Within the monitoring category of utterances, they included identifying comprehension failures as a subcategory. The frequency of monitoring statements was negatively correlated with the frequency of elaborations. This indicates that when learners realized that they did not understand the text, they did not produce explanations to overcome the impasse. In other words, participants seldom produced self-explanations when they realized that they had misunderstood the topic.

For kindergarteners or college students, generating their own explanation would be a hard work. Sánchez and colleagues (2009) explain that they are not always able to recover from an impasse through self-explanation. Besides the generation of the explanation, correction and completeness are very important. Incorrect self-explanations might be beneficial only if they are refuted by an external source of information, such as an instructional explanation. This implies that the correction and the completeness function can be a potential advantage of instructional explanations (Cho & Jonassen, 2012).

VanLehn et al. (2003) investigated a link between impasses, tutorial explanations, and learning. As was mentioned before, impasses take place whenever a learner recognizes an error and the need for a solution such as an instructional explanation. VanLehn and colleagues’ results revealed that instructional explanations containing impasses were associated with learning in two of the physics principles. In other words, explanations had no correlation with learning, but the explanations following an impasse did. The researchers noted that explanations could be more effective in the context of an impasse. It is inferred that instructional explanations are effective when learners do perceive them as a solution to their problems. In that case, they process the explanations in depth.

Sánchez et al. (2009) assessed the impact of an instructional explanation that explicitly addressed the two components of the mental model repair view, that is, conflict detection and repair. Regarding the first one, a specific aid called “Impasse-trigger” was provided. It was designed to provoke an impasse in learners by hinting a possible misunderstanding or openly pointing out an actual misunderstanding. Regarding the second component, a tailored explanation was provided after the presentation of the impasse-trigger. One group was provided with both impasse-trigger and tailored explanations and the other was provided with only identical explanation (no impasse trigger). The experiment group recalled more correct information, generated more transfer solutions, and showed fewer flawed ideas than the control group. As a result, impasse trigger worked as a conflict detector and tailored explanations worked as a repair. Learners are benefited by the combination of the two components.

Acuña, Rodicio, and Sánchez (2011) conducted similar research with the comparison of high and low prior knowledge groups. They focused on those kinds of instructional explanations that were provided to clarify or to correct the misunderstanding of learners. The study examined whether interaction effects existed between the kinds of instructional explanations and learners’ prior knowledge level. Results showed that low prior knowledge learners scored higher when explanations with indications of their misunderstandings were presented. High prior knowledge learners scored almost equally either with or without the indications. The researchers inferred that low prior knowledge learners had difficulties to grasp core ideas from rough explanations rather than indicated explanations. This supported Berthold and Renkl’s (2010) argument that trainings for focused processing should be provided in addition to presenting prompts for focused processing.

Considering all of these empirical studies, instructional explanations are most effective when they are presented right after learners face impasse. The instructional explanations function to correct and complete learners’ own explanations. The research of Calin-Jageman and Ratner (2005) shows that learning could be discouraged when a problem is presented first and learners are requested to explore self-explanation. The research suggests well-designed instructional explanations should be presented after learner impasse. This is one of the good answers to the comparison studies of different types of instructional explanations. Those results showed no significant difference, but they had limitations that they did not incorporate learner impasse in their study.

In addition, instructional explanations should be equipped with pre-designed impasse such as the impasse-trigger. Here is a quote from a teacher’s explanation and this is an example of impasse-trigger: “Usually the people who watch this presentation tend to elaborate a simplified conception of the plate collisions process; thus, probably you only saw that plates collide so the mountains are formed both in the Andes and in the Himalaya by the same principle. However, there are important differences between the two plate collisions that play a big role in clarifying what plate tectonics is (Berthold & Renkl, 2010, p. 34).” By providing possible misunderstanding and encouraging learners to detect a conflict, learners can be more actively reconstruct their knowledge.

As a strategy to improve instructional explanations, Jucks, Bromme, and Runde (2007) suggest avoiding the expert mistake. They point out that experts represent their knowledge in a specific way and, thus, they often do not envision the perspective of a novice learner. In other words, experts tend to fail to distinct discipline explanations and instructional explanations, and easily assume that novices are thinking the same way experts do. Therefore, it is very important for experts to generate instructional explanations that suit for novice learners (Koedinger & Aleven, 2007; Schoenfeld, 2010). In that sense, researchers have focused on the mental passivity of the recipient learners. They think mental passivity hinders learners’ full understanding of instructional explanations (Berthold & Renkl, 2010; Berthold, Röder, Knörzer, Kessler, & Renkl, 2011; Roelle & Berthold, 2013). As a consequence of failing full understanding, novice learners have erroneous belief that they have already understood the learning content, and they do not actively process instructional explanations (Charalambous, Hill, & Ball, 2011).

Mental Passivity

When should we provide information and assistance to learners and when should we ask learners to work on their own and to generate information, ideas, and solutions? Koedinger and Aleven (2007) called this problem the “assistance dilemma,” and claimed that the assistance dilemma is one of the fundamental unsolved problems in teachers’ delivery.

The research by Webb, Ing, Kersting, and Nemer (2006) may be a hint to solve the assistance dilemma. They suggested that learners’ follow-up activity after receiving explanations is the strongest predictor with respect to learning outcomes. The follow-up activity was predicted even stronger than the quality of the explanations themselves. This aligns with the empirical studies that compared various types of instructional explanations and found no differences. In a nutshell, this study proposes to provide instructional explanations and chances for active mental processing one after another.

Another study to minimize learners’ mental passivity has been conducted by Berthold and Renkl (2010). The researchers tried to improve the effectiveness of instructional explanations by fostering learners’ active mental processing. Three cases in this study entailed a kind of instructional assistance, “focused processing prompts.” The focused processing prompts were a text input box on a computer screen that requested learners to summarize central concepts and principles of the learning content. The results showed that the focused processing prompts group generated more elaborated explanations on domain principles and fewer incorrect statements. Also, it turned out that the focused processing prompts were effective particularly for novice learners.

In the Berthold and colleagues’ (2011) next study, “double-edged effects” of focused processing prompts were examined. Both positive effects for novices and negative effects for prepared learners were observed, and that was why they named the effects of focused processing prompts as “double-edged”. It was inferred that in the highly complex learning environment, in particular, focused processing of conceptual aspects of explanations fostered conceptual knowledge but at the same time hindered the acquisition of procedural knowledge.

Julian Roelle and Kristen Berthold (2013) paid attention to the lack of prior knowledge and utilized “training” to overcome the lack. Although focused processing was proposed to overcome learners’ mental passivity (Berthold & Renkl, 2010), learners often do not engage in focused processing. One of the possible explanations could be that lack of prior knowledge hinders spontaneous focused processing. Therefore, Roelle and Berthold assumed that if prior knowledge is learned beforehand, learners could be more engaged in focused processing. The results showed that the focused processing prompts fostered conceptual knowledge for novice learners, whereas the prompts hindered the acquisition of conceptual knowledge for trained learners. The researchers concluded that both prompts and training have advantages and disadvantages.

In the table below, Strategies and considerations for effective instructional explanations are summarized based on the empirical studies discussed in this section.

Table 1
Summary of strategies and considerations for effective instructional explanations

Strategies
  • When learners face impasse, providing instructional explanations is helpful to overcome.
(Sánchez et al., 2009)
  • Instructional explanations should be designed to include impasse.
(VanLehn et al., 2003)
  • Possible misunderstanding should be provided when delivering.
(Acuña et al., 2011)
  • To help users to detect conflict, impasse-trigger is useful in instructional explanations. Tailored explanations after impasse-trigger works as repairing function of learners’ mental model.
(Sánchez et al., 2009)
  • Instructional explanations work as correction and completeness function.
(Cho & Jonassen, 2012)
  • Instructional explanations are most helpful when presented right after learner impasse.
(VanLehn et al., 2003)
  • After presenting instructional explanations, give a chance for active mental processing.
(Webb et al., 2006)
Considerations and Cautions
  • Self-explanations should be carefully used. Without well-designed instructional explanations, users tend to face impasse and lose the chance to correct their mental model.
(Calin-Jageman & Ratner, 2005; Kendeou & van den Broek, 2007)
  • Try to avoid the ‘expert mistake’. Learners’ mental model is different from that of experts.
(Jucks et al., 2007)
  • Try to avoid learners’ erroneous belief (“I understand it!”). To accomplish this, encourage learners to actively process given instructional explanations.
(Charalambous et al., 2011)
  • Focused processing prompts are particularly useful for novice learners.
(Berthold & Renkl, 2010; Berthold et al., 2011)
  • Extra training intervention is needed when using focused processing prompts for novice learners.
(Roelle & Berthold, 2013)

In conclusion, recent empirical studies proposed several solutions to improve instructional explanations considering learners’ mental model in designing instructional explanations, and tried to minimize learners’ mental passivity in delivering instructional explanations. Instructors should prepare rich instructional explanations considering all possible learner confusions and misconceptions. This is not similar to a script of a play. Rather, it should resemble an online role-playing game scenario where users can open any doors and explore any destiny. In a delivery process, teachers keep making decisions on how fast and how deep they should present the learning content. Teachers may deliver only 1/10 of the prepared instructional explanations. Though, that is the nature of teaching like a role-playing gamer does not visit all the villages and meet all the game characters.

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