Deeper and Surface Learning

In 1972, Craik and Lockhart (1972) suggested the deeper learning terminology. They argued that deeper learning includes higher-level cognitive processing, as opposed to surface learning, where students use lower-level cognitive skills, such as memorisation or rote learning. Beattie et al. (1997) advanced this concept and described both approaches, deeper and surface learning in more detail:

The deep approach, which implies that a student learns for understanding, is characterised by students who (1) seek to understand the issues and interact critically with the contents of particular teaching materials, (2) relate ideas to previous knowledge and experience and (3) examine the logic of the arguments and relate the evidence presented to the conclusions. The surface approach, which implies that a student learns simply to memorise facts, is characterised by students who (1) try simply to memorise parts of the content of teaching materials and accept the ideas and information given without question, (2) concentrate on memorising facts without distinguishing any underlying principles or patterns and (3) are influenced by assessment requirements. (Beattie, et al., 1997, p. 3)

In 1976, Marton and Saljo originated the concept of deep processing to represent student's engagement with educational tasks, cited in (Laird, et al., 2008). In their view, the deep learning referred to moving beyond the surface understanding of the underlying knowledge. Throughout the 1970s and 1980s, other researchers investigated these terminologies, deeper and surface learning, and suggested strategies and features for each learning approach, see for example Biggs (1979), Entwistle and Ramsden (1982), Marton (1975), Pask and Scott (1972). In line with these researchers, Laird et al. (2008, p. 470) claimed that students who adopt deeper learning approach "read widely, combine a variety of resources, discuss ideas with others, reflect on how individual pieces of information relate to larger constructs or patterns, and apply knowledge in real-world situations".

The scope of this section is to differentiate between these two approaches to learning. An in-depth approach, which is described as meaningful learning, i.e., students are sense makers of what they learn, while the surface approach is represented by the habitual repetition of the content to be learned (Biggs, 1987; Entwistle & Ramsden, 1982; Marton, 1983).

Rosie (2000, p. 45) stated that “deep learning is not a function or attribute of the learner but is a strategy that people can adopt”. The student adopting an in-depth approach to learning concentrates on grasping the taught material, links elements to each other, new concepts to prior knowledge, and concepts to real-life situations. On the other hand, the student who adopts a surface approach favours to memorise discrete experiences and deal with a specific task in isolation from other tasks, concepts and real- life situations (Chin, 1999).

In 2013, deeper learning was adopted by the Hewlett Foundation (2013), who claimed that America’s schools could not prepare students sufficiently to overcome the future's challenges. The Hewlett Foundation addressed six values or capabilities associated with deeper learning:

i. Master the academic content

ii. Think critically and answer complex problems iii. Consider collaborative learning

iv. Effective communication v. Know how to learn

vi. Develop academic mindsets

The Hewlett Foundation claimed that these capabilities apply to higher education and online environments, as online learning is becoming more popular.

Conley (2012) described deeper learning as “readiness across multiple dimensions, with an alignment of student skills, interests, aspirations and their post- secondary objectives”. According to Conley (2012), this readiness is outlined in three interrelated categories; Think: key related to cognitive strategies that involve problem- solving, research, and interpreting data. Know: key related to content knowledge; it includes structuring knowledge in core subjects and the ability to acquire knowledge.

Act: key related to learning skills and students’ ownership of their learning.

The National Research Council (NRC (2012)) outlines three broad domains of competence. First, the cognitive domain, which involves thinking, reasoning and critical thinking. Second, the intrapersonal domain, which includes self-management, including the ability to regulate behaviour. Third, the interpersonal domain, which represents the ability to express ideas to others, and also interpreting ideas from others. The NRC domains strongly echo the Think, Know, Act competencies that were suggested by David Conley and adds some interpersonal skills as well (VanderArk & Schneider, 2012).

“The cognitive engagement of students with learning material to the extent that they uncover deeper meaning and associations, appraise material critically and generalise their learning from one context to another” (Day, et al., 2010, p. 3). This idea is supported byVanderArk and Schneider (2012), who defined deeper learning as the

process through which a student displays what was learned in a specific situation and applies it to new tasks and conditions; in other words, learning for transfer.

The NRC (2012) proposes that pedagogy is a crucial component of deeper learning, i.e., learning for transfer:

Emerging evidence indicates that cognitive, intrapersonal, and interpersonal competencies can be taught and learned in ways that support transfer. […] Teaching that emphasises […] not only content knowledge, but also how, when, and why to apply this knowledge is essential to transfer. (National Research Council, 2012, pp. 8, 23)

The NRC (2012) advises several policies to expedite deeper learning, such as using various shapes and forms to represent concepts and tasks; foster discussion, questioning and illustration; involve learners in challenging assignments; teach with models, examples and instances; motivate students, as well as the use of formative assessments. Thus, schools are encouraged to re-plan education and develop effective rubrics and assessments that can measure deeper learning skills. For instance, schools need to leverage the use of digital technology in learning, lengthen learning time and develop teachers and students’ technical skills. In turn, this means that the traditional boundaries of learning continue to expand and collapse as mobile technologies shift learning from a place-based to service-based learning. The Alliance for Excellent Education (AEE (2012)) described this as a culture shift from a teacher-centred to student-centred pedagogy.

Previous studies in science education propose that a student’s learning approach impacts the learning outcome. For instance, BouJaoude (1992), Cavallo and Schafer (1994) argued that an in-depth approach to learning is accompanied with a more extensive coherent knowledge, fewer misunderstandings, and interrelated and better understanding of the concepts. In a 2005 study, Smith and her colleagues investigated the association between teaching methods and students' learning outcomes; their findings showed that "a majority of the teachers (64 per cent)… aimed instruction and assignments toward surface learning outcomes" (Smith, et al., 2005, p. 205). Moreover, their findings showed that most of the students (78 per cent) adopted a surface approach to learning. Smith and her colleagues argued that these findings were due to the

instruction implemented by the teachers, which appeared in students memorising and recalling fundamental knowledge without perception. These findings support the claim of Hill and Woodland (2002), who suggested that deep learning is not a one-way process, but a two-way dialogue between effective teaching and attentive learning.

To reach a better understanding of the depth of teaching and learning outcomes, Biggs (1979), Biggs and Collins (1982) developed a research-based framework. In this framework, Biggs and Collins represent five levels of complexity of the learning outcomes:

i. The pre-structural level represents unrelated informational factors.

ii. Uni structural level related to students’ abilities to create relationships between various fundamental factors without understanding the meaning.

iii. Multi structural level related to students’ abilities to create connections among complex factors and information networks, but the meaning of the connections still is missing.

iv. Relational, at this level, students comprehend the relationships between various informational factors.

v. Extended abstract, students move from relational understanding to a higher level of thinking, transferring and generalising.

Biggs and Collins claim that by using their framework, teachers can decide whether learning outcomes and teaching practices foster more in-depth learning approaches.

Rosie (2000) investigated the learning activities of postgraduate students using web-based resources and investigated whether these resources lead to deeper learning. Rosie (2000) adopted a dialectic approach to developing web-based instructional resources. In the dialectic approach, students worked on a task, argument and alternative ideas. Rosie proposed that applying dialectic approach reduces the differences between actual educational outcomes and professional expectations, which fosters deeper learning.

To ensure fostering deeper learning, some researchers recommended the use of more synchronous resources for students. For instance, Offir et al. (2008) claim that synchronous resources support active learning and students’ understanding and

engagement, which contributes to deeper learning approaches. "When the students are more active in the learning process, the material becomes more relevant and more significant for them, they remember it better, understand it, and as a result, their achievements improve" (Offir, et al., 2008, p. 1181).

Chin (1999, p. 240) suggested five new categories to differentiate between deeper and surface learning; "generative thinking, nature of explanations, questioning, metacognitive activity, and approach to tasks".

Generative Thinking

This category outlines students’ capability to create an idea without receiving a ready-made clarification or solution to a specific problem, mainly when the problem is unusual and needs moving beyond recalling fundamental facts.

Nature of Explanations

This category refers to students’ ability to produce an explanation to a specific phenomenon or a problem that can link the macro and micro levels. In other words, the ability to explain the effects of non-observable, invisible, entities in a specific phenomenon and create relationships between abstract factors, such as the photon’s frequency and electric current in the photoelectric effect.

Questioning

Questions associated with surface learning are concerned with basic knowledge, requiring only a recall of facts. Such questions are often closed questions that have unambiguous answers. They typically are linked to the knowledge contained in the textbook or any simple observation about a phenomenon. On the other hand, questions associated with deep learning reflect students’ ability to link several concepts to find the answer to a specific problem. They concentrate on "explanations and causes, predictions, or on resolving discrepancies in knowledge" (Chin, 1999, p. 242). This kind of questions requires higher-order thinking skills as students need to relate the new and existing experience, combine complex and divergent knowledge from various sources, and develop internal relationships between diverse aspects of the latest knowledge in their attempts to understand.

Metacognitive Activity

This category describes students’ use of awareness and evaluative approaches that indicate their strategy of thinking. It has been noticed by Chin (1999) that the students, who adopt a deep approach to learning demonstrate higher cognitive self- evaluation and control of their learning, unlike the students who use the surface learning. Moreover, Chin (1999) stated that students with deep learning could evaluate their ideas, detect their mistakes and self-corrected them, consider a range of potential solutions, endeavour to grasp alternative approaches, and acknowledge limitations in their ideas and criticise them.

Approach to Tasks

A student, who adopts a deep approach to learning, shows more persistence in following up a task before moving to another one. In the case of using the surface approach, the student gives up an idea as soon as it did not work. Moreover, when utilising an in-depth approach, the student attempts to create ideas, whereas one applying a surface approach relies on ideas generated by others, such as the teacher or other students.

Table 7 is based on the research conducted by Chin (1999); it shows a summary of the differences between deeper and surface learning.

Deeper learning Surface learning

Students generate their ideas spontaneously Students repeat the ideas they memorise Students’ responses are more precise Students’ responses are general Students can describe non-observable entities

(microscopic) and cause-effect relationships between microscopic and macroscopic entities.

Students’ abilities are limited. They can describe observable entities (macroscopic)

roughly. Students display higher cognitive self-evaluation

and control of their learning

Students cannot give accurate cognitive self-evaluation and have poor capability of

controlling their learning Questions associated with a more in-depth approach

to learning focus on demonstrations, reasoning, predictions, or concluding discrepancies in knowledge lead to an advancement in conceptual

understanding.

Questions associated with the surface approach to learning referred to basic

knowledge.

2.3.6.1 Deeper Learning and Instructional Design

Instructional designers start with the analysis of the learners, then determine learning goals, arrange learning activities and finally develop and implement assessment procedures. All these activities are driven by the learning theories and instructional methods and strategies. (Czerkawski, 2013, p. 10).

McGee and Wickersham (2005, p. 2205) outline the relationship between deeper learning and instructional design by stating that "the deeper learning principles indicate a higher degree of learner control, decision-making, and organisation….. thus, requiring well conceptualised instructional design". This view is backed by Du et al. (2011), who confirmed the significance of instructional design in promoting more in-depth learning.

To design deeper learning environments, instructional designers need to consider the following factors (Offir, et al., 2008; Chapman, et al., 2005; Smith & Colby, 2007; McGee & Wickershame, 2005):

i. Supplying students with authentic learning expertise. Deeper learning "requires that the learning design takes into consideration the learner's context of practice, ways of learning, as well as experience in the world" (McGee & Wickershame, 2005, p. 2206). Therefore, it is essential to link content knowledge with real-life situations.

ii. Challenge students by learning activities that require higher-order cognitive skills, such as problem-solving, creating relationships, evaluation and analysis. Smith and Colby (2007) argue:

Students, who move beyond surface learning consider any given task as a series of internal rhetorical questions: What do I know about this subject? How does this information relate to what I already know? What is the broader implication or significance of what I've learned? (Smith & Colby, 2007, p. 207).

iii. Developing a meaningful dialogue between students. A dialogue takes place in environments through which members are open to other students' share their

point of views, which move students to common ground (Chapman, et al., 2005). Offir et al. (2008) suggest that the dialogues have a positive impact on students’ learning as they encourage students to adopt an in-depth approach to learning. This idea was endorsed by Smith and Colby (2007, p. 207) who claimed that "one way to accomplish (deeper learning) is to engage all members of the community in intentional, substantive, and inclusive dialogue about student learning". iv. Monitoring teaching and learning activities: Smith and Colby (2007) noticed in

their study that the design of specific materials and tasks can limit students to surface learning. If a learning environment involves tasks that support surface learning, deeper learning consequences cannot be anticipated. Therefore, courses and activities need to be periodically revised to incorporate tasks resulting in more profound learning experiences.

v. Generating periodic feedback using formative assessments: Feedback about student's learning from the teacher or other students is estimated to be one of the most powerful strategies that foster student’s accomplishment (Rushton, 2005).

To foster deeper learning, instructional designers need to focus digital educational resources on new forms and methods of education; offer interactive content; consider the concept of differentiation and individualisation; take into account students’ cultural experience; provide students with learning activities that guide them to construct their own knowledge and solve real-world problems; promote both types of learning, independent and social learning, including social constructivism (Makarova, 2018).

2.4 DIGITAL TECHNOLOGY, DEEPER LEARNING AND