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27th Annual SCUTREA conference proceedings 1997

Crossing borders, breaking boundaries : Research in the education of adults

Identifying groups of learners through the use of learning strategies

Rita C. Kolody, Medicine Hat College, Canada
Gary J. Conti, Montana State University - Bozeman, USA
Suzanne Lockwood, Montana State University - Northern, USA

Since the classic work of Houle (1961), two distinct strands of research have emerged in the field of adult education. The orientation, focus, philosophical basic, and methodology of these two strands has been different. One strand has focused on the programme planning element of adult education. Its concern has been with formal programmes and those who participate in them. Research findings from these studies have direct applicability by administrators interested in establishing a flourishing adult continuing education programme. Houle's learning orientations have served as the conceptual basis for this line of inquiry and much of the inquiry has centred around the work of Boshier (1971) and his Education Participation Scale. While much of the research has focused on those who participate in the formal programmes, some has also investigated the non- participants (Scanlan and Darkenwald 1984). Regardless of the exact audience being investigated, this line of inquiry tends to ask research questions from a psychological perspective and relies on quantitative methods to measure the degree of participation.

The other strand focuses on the individual learner. Rather than being preoccupied with the learner's participation in formal educational programmes, researchers in this camp have been intrigued with the concept of self-directed learning and with how adults learn in a variety of informal, real-life situations. Drawing heavily on sociological concepts, this group is grounded in phenomenology and pays special attention to the context in which the learning is taking place. The research methodology of choice for this group is qualitative in nature and individual development and empowerment are the outcome goals for learners in this approach. This group prefers to use the verb 'learning' rather than the noun 'education'.

Members of these two strands ask fundamentally different questions in the field of adult education, and the field is stronger because of this diversity. The groups differ in almost every aspect, one difference being that the participation-focused group has had a clear conceptual model upon which to base their inquiry. This has been Houle's learning orientations with the three orientations toward either goal, activity, or learning purposes. The learning-focused group has not had such a typology around which to organise its research. However, that may now be changing. Collectively, recent research in the area of learning strategies has yielded evidence of five distinct groups of learners that exist in most learning situations and that cut across most demographic variables. Thus, these findings have the potential of providing a typology for learning similar to the typology which Houle's learning orientations provided to participation researchers.

Regardless of the type of setting, learners use various strategies to accomplish their learning needs. Learning strategies are

the techniques and skills that an individual elects to use in order to accomplish a specific learning task ... Such strategies vary by individual and by learning objective (Fellenz and Conti, 1989, 7-8).

Since the recent development of the Self-Knowledge Inventory of Lifelong Learning Strategies (SKILLS), researchers such as Hays (1995), Hill (1992), McKenna (1991), Moretti (1995), Strakal (1995), Yabui (1992), and Conti and Kolody (1995) have found that various groups of learners can be distinguished by the learning strategies which they use.

The purpose of this study was to expand the investigation of this growing area of study by examining and describing the learning strategies by adult learners at two-year colleges in Alberta, Canada. Most of the previous studies had in this area utilised populations that had a specific focus. This study solicited a broad population from several diverse public community colleges in order to gather a disparate data set in order to describe the learning strategies used by a large group of adults in order to determine if patterns existed in how they learn. Building upon a learning strategies study initiated at Medicine Hat College (Conti and Kolody 1995), five Canadian two-year community colleges agreed to co- operatively conduct this study with the technical assistance of the adult education staff from a US university. In addition to Medicine Hat College, these schools included Grande Prairie College, Keyano College, Mt. Royal College, and Red Deer College.


This research project consisted of two parts. The first part was causal- comparative in nature to investigate the relationship of learning strategies to a variety of educational and demographic variables. This stage of the research was approached deductively. Groupings which were hypothesised as potentially having an influence upon how people used learning strategies were imposed upon the data. The multivariate technique of discriminant analysis was used to determine if the groups could be discriminated from each other based upon the interactive effects of the various learning strategies.

The second part was descriptive and was approached inductively. Cluster analysis was used to identify the groups which inherently existed in the data (Conti 1996). To help name and describe these clusters, analysis of variance and discriminant analysis were conducted. Since five distinct groups of learners were identified by this quantitative process, individual and group interviews were conducted to collect supplementary qualitative data to further assist in describing the clusters. These interviews elicited responses from the participants that described their learning patterns and preferences and that related their learning to actions of teachers. Individual and group interviews were held with each cluster of learners; 28 group and 23 individual interviews were conducted.

Learning strategies were measured with the Self-Knowledge Inventory of Lifelong Learning Strategies (SKILLS). This valid and reliable instrument consists of real life learning scenarios with responses drawn from the areas of metacognition, metamotivation, memory, critical thinking, and resource management (Conti and Fellenz 1991). Each of the five areas consists of three specific learning strategies: Meta-cognition Planning, Monitoring, and Adjusting; Meta-motivation Attention, Reward/Enjoyment, and Confidence; Memory Organisation, External Aids, and Memory Application; Critical Thinking-Testing Assumptions, Generating Alternatives, and Conditional Acceptance; and Resource Management-Identification of Resources, Critical Use of Resources, and Use of Human Resources. SKILLS has two forms of six scenarios; both forms were used in this study. From these, respondents pick four scenarios that are most meaningful to them.

Data were collected by administering SKILLS to a representative sample of students at each of the five participating colleges in Alberta. At each college a local research assistant from the faculty identified a sample which was representative of that college, and each college was randomly assigned one form of SKILLS. Additionally, demographic and educational information was gathered to further analyse the relationship between these factors and learning strategies. The sample included 1,143 learners who ranged in age from 17 to 71; 70.5% were female, and 29.5% were male.


The overall profile for the students throughout the province revealed a divergent group of learners; no single learning strategy area or specific learning strategy was predominant. The possible range of scores for the learning strategies areas is 12 to 36. All the group means were near the middle of this range: Metacognition 23.2; Metamotivation 22.9; Memory 24.1; Critical Thinking 23.9; and Resource Management 25.5. Likewise, the individual learning strategies, which have a range of 4 to 12, had little divergence with means that varied from 7.04 to 8.84.

Discriminant analysis was used to analyse the relationship between learning strategies and various demographic and educational variables. Discriminant analysis is a multivariate procedure which is used to discriminate between different groups of people by placing them into groups and investigating if they can be distinguished by a set of discriminating variables (Conti 1993; Klecka 1980). Unlike Hill (1992) who found a meaningful discriminant function which distinguished the group of learners at Montana's tribal colleges with the lowest grade point average from the group with the highest grade point average, learning strategies as measured by SKILLS were not useful in discriminating similar groups of learners in the Canadian two-year colleges. Likewise, only weak differences were found when the learners were grouped in the areas of gender, programme, and age. Consistently, each of these analyses explained only about 10% of the variance that could be explained beyond mere chance.

However, cluster analysis was more successful in explaining the data. Cluster analysis is a multivariate statistical procedure that seeks to identify homogeneous groups or clusters in the data (Aldenderfer and Blashfield 1984, Chapter 1). Its strength lies in its ability to examine the person in a holistic manner (Conti 1996). Cluster analysis produced a solution with five clear and distinct clusters of learners. Based upon quantitative analysis using analysis of variance for each of the learning strategies and the other demographic variables when the learners were divided into their clusters and based upon the interviews, these fairly equal sized clusters were named Navigators (259), Monitors (266), Critical Thinkers (223), Engagers (236), and Networkers (199).

Each of the five distinct groups of learners have explicit preferences for learning strategies and learning is enhanced when teaching strategies and learning environments are congruent with the prominent learning strategy specific to that group. As learners in this study reflected upon the specific preferences for their group, they offered insightful recommendations for teachers.

The Navigator cluster contains the highest number of university transfer students along with the students with the highest grade point average. It is composed of learners who rely heavily on the meta-cognition strategy of Planning. Thus, these focused learners chart a course for learning and follow it. This group is also higher than other groups in its preference for the Resource Management learning strategy of Identification of Resources; thus, its members know how to locate and use the best information. They also frequently use the Memory strategy of Organisation to structure or process information so that the material can be better stored and retrieved. As structure and organisation is crucial to the success of these learners, teachers can enhance learning by communicating expected learning outcomes and by providing outlines, schedules, and deadlines.

Monitors are the learners who most often use the Meta-cognition strategy of Monitoring as they review plans, check to see if they are on task, and compare their progress to accepted standards or models. This group contains older students who rely heavily on the Resource Management strategy of Critical Use of Resources to help in the learning process; this process includes using appropriate rather than available resources and contacting experts or other secondary sources. These learners also use the Meta-motivation strategy of Attention such as avoiding distractions and setting time aside for learning to stay focused on the material. Specific to this group, these learners are most successful and are able to best monitor their learning progress when visual models and standards are provided as a basis for comparison.

Critical Thinkers are those students who make heavy use of the Metacognition strategy of Adjusting their learning process as well as the Memory strategy of Memory Application, which involves using mental images or other memories to facilitate problem solving. This group also relies heavily on all the strategies in the area of Critical Thinking. They Test Assumptions to evaluate the specifics and generalisability within a learning situation; they Generate Alternatives to create additional learning options; and they are open to Conditional Acceptance of learning outcomes while keeping an open mind to other learning possibilities. Provision for individuality and creativity in completing assignments and projects is the key for successful learning for Critical Thinkers. As these learners instinctively generate alternatives, learning is enhanced with opportunities for hands-on learning and experimentation. Because learners in this group place little importance on memorisation, they are best evaluated with open-ended questions and problem-solving activities.

The Engagers are the passionate learners who love to learn and learn with feeling. This groups relies heavily on the Metamotivation strategies of Reward/Enjoyment to anticipate the value to one's self for learning or having fun with the learning activity and of Confidence to reassure their belief that they can complete the learning task successfully. This group also uses the Memory strategy of using External Aids such as lists to reinforce memory. Since this group learns best when they are actively engaged in a meaningful manner with the subject matter, the environment, and the teacher, educators should provide Engagers with opportunities that encourage learning projects based on individual student interests. Teamwork and group projects that focus on process as well as product can also reinforce the learning strategy of reward/enjoyment required by these learners.

The Networkers frequently use the Resource Management strategy of Using Human Resources, which includes dialogues, discussions, and networking to integrate others into the social and political processes of learning. They also make heavy use of the Memory strategy of Memory Application such as using mental images or other memories to facilitate problem solving. Interaction is the key to learning for this group, so educators should provide an environment that allows for brainstorming, teamwork, and discussion of opposing or different viewpoints. As these learners make heavy use of human resources, teachers can enhance their learning by including guest speakers and media to present expertise in various subject areas.

Discriminant analysis was used to identify the process that distinguishes the five clusters of learners from each other and to generate a formula for placing individuals in the groups (Conti 1996). The discriminant function produced by this analysis was 95.5% accurate in placing the 1,143 learners in their correct clusters; this is a 75.5% increase over their chance placement of 20%. Two of the four discriminant functions produced by the analysis each accounted for over 50% of the variance that existed in the data. The first function accounted for 62.03% of the variance, and the second one accounted for 56.08% of the variance. The process that discriminated the groups from each other in the first function was an internal versus external view of the learning process by the learner. In this function, the Metamotivational strategies of Confidence in learning and Reward/Enjoyment with learning were contrasted with the Resource Management strategy of Identification of the best learning sources. While some learners emphasised their own motivational factors for learning, others gained their security in learning by having the proper learning resources. This first function was named Locus of Control for Learning. The second function, which described another process that discriminated the groups from each other, paired Attention by focusing on the learning materials and Planning the best way to learn against the strategies of Memory Application by using techniques such as mental images and Conditional Acceptance of learning outcomes. Thus, this function distinguishes between those with a preoccupation with what needs to be learned and how this is going to be accomplished and those who have mental flexibility with the learning process. The second function was named Structure for Learning.


This study adds to the growing literature base on learning strategies and contributes to a deeper understanding of patterns and divergence in adult learners. Clearly, distinct groups do exist of learners who have particular preferences for different patterns of learning strategies for attacking learning problems.

Numerous discriminant analyses were conducted to explore hypothesised differences in known groups of learners. Although some differences were found among the learners, no strong patterns were found. The inability to find differences using discriminant analysis suggests that imposing sense upon the data through preconceived groupings is not the best way to uncover differences in uses of learning strategies by disparate groups of learners. Instead, multi-variant techniques such as cluster analysis which allow the data to expose its own patterns are more productive.

The findings from this study are supported by other learning style research being conducted at the Center for Adult Learning Research at Montana State University. Data from 422 financial planners in the United States were combined with the data set from this study and the clusters were recalculated; although 37% more variance was introduced, the clusters from this study were reproduced (Conti, Kolody and Schneider 1997). Likewise, other studies with more specific populations have produced results similar to this study. Using nursing students in Montana, Lockwood (1997) found four groups of learners. Using Air Force personnel at the Pentagon, Korinek (1997) also found four groups. Using tribal people from the community and from a community college on the Fort Peck Reservation, Bighorn (1997) also likewise found four groups. All of the groups are remarkably similar to the five found in this study. Since the populations for these studies is more concentrated than the province-wide community college population of this study, the four groups from these other studies appear to be subsets of five from this study.

The five distinct clusters that emerged in this Alberta study may be a new typology with major implications for teaching, diagnosing, and counselling of adult learners. In fact, the findings from this study suggest that a general typology of learners exists which cuts across the demographic variables which researchers typically use to classify learners.

As these Canadian colleges have co-operated to follow Schön's suggestion of being reflective practitioners who can create their own knowledge base, they may have uncovered a general model related to the strategies used by adult learners. Besides jointly conducted training sessions for the college faculties, the findings from this study have encouraged the faculty and students associated with the Center for Adult Learning Research and the adult education graduate programme at Montana State University to expand their research efforts related to learning strategies and to duplicate the overall design of this study with various populations of adult learners. When a broad enough sample can be collected which will be representative of that diverse and elusive target population referred to as the adult learner, a similar cluster analysis will be conducted. Such an analysis will disclose if this five-cluster solution is a general model for adult learners or if it is more contextually specific to Canadian learners in Alberta. In the meantime, this study has demonstrated that as in previous studies, SKILLS appears to be an effective instrument for identifying adult learning strategies and that the concept of learning strategies is a productive tool in the pursuit of a better understanding of adult learning.


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