Algorithmic and conceptual teaching approaches

Algorithmic or symbolic instruction promote memorising and rote learning, which in turn is likely to limit students’ ability to reflect on the what, how and why of what they learn (Haidar and Naqabi, 2008). When students memorise facts without questioning them, they are not questioning their thought process and therefore they cannot develop their metacognition because rote learning takes place when learning does not occur at the conceptual level (Haidar and Naqabi, 2008; Cardellini, 2002).

An instructional approach that emphasises conceptual understanding usually challenges students to reflect upon their learning; and in so doing helps students to develop their metacognition (Robinson, 2003; Cardellini, 2002). It is reasonable to deduce that when this approach is applied in teaching stoichiometry, it allows students to develop an awareness of connections that exist across a number of basic concepts, ideas, rules and principles. When students see connections across related ideas and principles, they do not need to memorise formulas, rules or principles, instead they can derive them by applying their conceptual understanding (Robinson,

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2003). For example, when students understand the law of conservation of mass or the law of action of masses, they are able to compute the masses of both reactants and products using the mole concept and reflect on the solutions; they do not have to memorise the formulas. Haidar and Naqabi (2008) argue that when students reflect on the solutions of their stoichiometry problems and at the same time question their learning, they avail to themselves an opportunity to develop their metacognition.

A learning environment which integrates stimulation of students’ interest and active learning as well as collaborative learning and peer tutoring often promotes metacognitive thinking skills (Ellis et al., 2014). Working in collaborative groups or pairs allows students an opportunity to explain to each other the steps they followed to solve the problem and the reason they chose the strategy they followed. Such opportunities where peers explain to each other strategies for solving problem tasks allow strategy modelling to take place which is also part of explicit instruction which promotes metacognitive awareness (Sharlach, 2008).

To summarise: Research findings suggest that in general teachers of stoichiometry adopt an algorithmic approach in lessons about stoichiometry (Haidar and Naqabi, 2008; Gabel, 1999). Teaching students stoichiometry using an algorithmic approach is unlikely to promote the development of metacognitive skills, while a conceptual developmental approach is likely to help students to reflect on their learning thereby availing to themselves opportunities to develop their metacognition (Haidar and Naqabi,2008; Robinson,2003; Cardellini,2002). Thus, discovering the instructional methods used by the three teachers could help to understand the metacognitive abilities shown by the students in the pre-test assessments, provide information about the instructional methods used by the teachers and might also give insights into the pattern of findings at the post-test.

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7.1.3 Motivation strategies

In Chapter 6, a link between motivation and metacognitive awareness was discussed. Three components of motivation were discussed; expectancy component, value component and affective component. The expectancy component concerns the student’s ability to answer the question ‘Can I do this task?’ (Pintrich and De Groot, 1990). The various attributes of the expectancy component of motivation are linked to the learner’s metacognition (Ambrose, Bridges, DiPietro, Lovett, and Norman, 2010; Pintrich and De Groot, 1990). The learning environment and how teachers structure and deliver the learning activities can have an impact on students’ expectancy component of motivation (Ambrose et al., 2010). For example, a teacher who starts by giving students easy tasks to build their confidence is likely to have a positive impact on the students’ expectancy component of motivation as the task increases in difficulty (Efklides, 2011; Ambrose et al., 2010).

The value component of motivation concerns the student’s perceived value in carrying out the learning task. In other words, the learner must answer the question; ‘why I am doing this task?’ (Pintrich and De Groot, 1990). There often is increased metacognitive activity and engagement with the task when the student is motivated to carry out the learning task (Ames and Archer, 1988; Nolen, 1988; Paris and Oka, 1986). The teacher can play an important role in shaping the students’ value component of motivation by making a difficult learning task more interesting or manageable by using different strategies. For example, the teacher could pair up students to facilitate reciprocal or peer tutoring.

The affective component of motivation has to do with how students feel about the learning task. In other words, it’s about a learner asking ‘How do I feel about this task?’ (Pintrich and De Groot, 1990). As reported in Chapter 6, generally students

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believe that stoichiometry is a difficult area of chemistry and this subject belief can result in a dislike of stoichiometry (Efklides et al., 1999; Schwarz, 2010). Again, as already observed, teaching strategies can play a significant role in helping students develop a positive affective component of their motivational orientation. As a result, discovering more about the way that the teachers of the three groups increased the motivation of their students could provide a broader context to the research and might also help to provide explanations for the findings reported in Chapter 5.

Research Questions

The overall aim of carrying out the interviews with the teachers of the three groups was to obtain a better understanding of the usual instructional strategies that they used when teaching stoichiometry (i.e. the strategies they used before the research intervention). The first reason for collecting this information was to see whether the similarities and differences in teaching could help to explain the findings reported in Chapter 5. The second reason for collecting this information was to better understand the context of the research and whether the teachers used instructional strategies that were similar to those that have been previously reported. Consequently, the three research questions concern the teaching prior to the intervention:

1. What instructional strategies did the teachers of the three groups use to help students with stoichiometry?

2. What instructional strategies did the teachers of the three groups use to help develop their students’ metacognitive knowledge and skills?

3. What instructional strategies did the teachers of the three groups use to motivate students when teaching stoichiometry?

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7.2 Method

7.2.1Participants

Three teachers were interviewed. The teacher of Group A is referred to as teacher A and that of Group B as teacher B while that of Group C is referred to as teacher C. The usual chemistry teachers of groups A, B and C taught these groups in the research study, although the teacher of Group A had only being carrying out these duties for a term. It was not possible to find different teachers to teach the groups, although this would have been an advantage.

7.2.2 Procedure

Interviews were conducted in a quiet place chosen by each teacher. For example, teacher A and B had access to a quiet office on their respective campuses, while teacher C preferred to be interview in her laboratory. The interviews lasted between 20-30 minutes depending on how engaging the interviewee was during the interview. All interviews were carried out using similar questions (see Appendix 5).The opening question was always Can you just talk me through how you teach stoichiometry, what’s your approach and how do you develop the topic. Follow up questions depended on the response given by the interviewee and these along with other independent questions were used to build up the conversation.

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7.3 Results