Examining Home Learning Environments

Abstract

This study uses a methodology originally developed by education researchers examining the homework environment and homework achievement of school pupils. We adapt the approach to make it relevant to higher education, in this case to Geography and Earth Science students. We find that environmental and personal components, significantly influence levels of student achievement. The rationale for this research is that as our demands for personal study increase (due to the rise in distance learning and WWW- based learning) we should develop strategies to improve the relationships between out-of-class learning environments and individual learning styles.

Introduction

A growing literature exists on the relationships between the learning environment and the achievement of learning outcomes (Fraser 1998). However, research into the influence of the learning environment on learning strategies is relatively new (Wierstra et al 1999). The overall aim of this kind of investigation is to identify the relationship between all aspects of the environment and the student, with the intention of improving the learning process. To date, much of the work in this area has been conducted on the in-class environments of school-age communities. Higher Education is differentiated from primary and secondary levels by its greater emphasis on personal study - termed ‘homework’ at these lower levels. Geography and Earth Science approaches are typical. It is essential that students follow up contact hours with reading, prepare for assignments and research dissertations, whilst managing their own study environments. Thus there is strong justification for examination of the influence of out-of-class learning environments as we move into a time where wider participation via e-based tuition and distance learning is promoted. Hong (2001) states that efforts have been made to adjust classroom environment to students’ in-school learning styles and cites Boulmetis and Sabula (1996) and Caudill (1998) amongst others. Similar attempts should be made to encourage students to improve the environments in which they study in their own time.

Many of the factors which affect in-class learning environments can be controlled by the tutor and, to some extent, by the learners themselves. These include physical ‘tangible’ factors such as seating, temperature, lighting, visual aids and the existence of adequate work surfaces and also ‘nontangibles’ academic context, motivation, peer influence and discipline. On the other hand many other factors will influence the effectiveness of personal study; these can be grouped as:

1. the cognitive and personality characteristics of the student (e.g. individual preferences of time, place and conditions);

2. the type of work being done (e.g. assessed, note-taking, research);

3. other influences on the process of learning outside the University environment (e.g. the impact of culture and subculture, paid work, social commitments, friends, family and flat-mates).

This preliminary study investigates the importance of aspects of the home learning environment on achievement. We base this work on the premise that HE has much to learn from the pedagogic research undertaken on school communities. This project relied heavily on a methodology developed by Hong and Milgram (2000) to evaluate the homework style of school (seventh grade) students in the USA. A homework scale was modified to be appropriate to an HE population. This involved for example omitting ‘parents’ as an influence on the home learning environment (although increasingly in HE the wisdom of this omission could be challenged).

Methodology

The Personal Study Preference Questionnaire (PSPQ) (termed Homework Preference Questionnaire by Hong and Milgram) was used to measure how students preferred to learn at home. It was distributed to 103 First and Second year students of Geography and Earth Science at University College Northampton. In the questionnaire eighty items are rated on a five point Likert scale to provide 18 scores that correspond to 18 personal study components. Likert ratings were based on the results of a pilot study with a group of six respondents. Items were worded so that low point scores on the Likert scale were potentially associated with ‘good learning practice’ (for instance, ‘I like to work in a quiet place’). Items were subdivided by motivation and preference. Motivation items assess the source and strength of the motives that explain the initial student activation (Is it immediate? Is it last minute? Is it outcome-oriented?). Preference items investigate how the learner then proceeds until study is completed. For twelve of the components a high score for the relevant component indicates a high preference (Self-motivated, Tutor-motivated, Persistence, Responsibility, Structure, Order, Authority figures, Auditory, Visual, Intake, Kinesthetic and Mobility). For instance, a student scoring high on ‘Structure’ prefers those activities that are well-defined and specific to a particular assessment rather than general research and background reading. Similarly, high scores on the ‘Visual’ component would reflect a liking of web-based tuition and poster-based activities.

The remaining six components are environmental. These are scored on a bipolar scale with high scores indicating a preference for the second of each of these component pairs - silence/sound, dim/bright illumination, cool/warm temperature, informal/formal design, alone/with peers, change place/same place. For instance, ‘Informal/formal design’ refers to the choice between hard chair and desk or a sofa or bed. The internal consistency (Cronbach’s alpha) of each PSPQ component ranged from 0.48 to 0.86. The internal consistency estimates of four components (Structure, Order, Authority Figures and Tutor-Motivated) were below 0.60 and as a result these should be interpreted with caution.

In common with the original procedure of Hong and Milgram (2000) the sample was divided into groups according to:

1. A subjective method based on self-perceived achievement;

2. An objective method based on previous assessment scores.

Self perceived achievement was measured using five items which were included within the PSPQ. These asked students to agree/disagree (using a fivepoint scale) on questions such as ‘I try to get the highest grade possible in all assigned work’ and ‘I try to read everything on the module reading lists’. The students were divided into three groups on the basis of their scores on these five items. Those attaining total scores above the 33^rd percentile of the sample thus became the ‘high (self-perceived) achievers’ and the other two groups were the ‘middle (self-perceived) achievers’ and ‘low (self-perceived) achievers’.

The objective method used previous class assessment scores to divide the sample based on actual achievement, in the same way as the self-perceived method above. One methodological issue here should be expressed and that is only a limited amount of assessed work (two pieces) was used. This should be treated with caution as in most institutions First year work does not require more than a ‘pass’ as the marks do not contribute to the final degree classification.

Results

(a) Self-Perceived

Statistically significant differences in PSPQ scores (at 95%) were found between the three levels of self-perceived achievement. The differences were most apparent in 7 out of the 18 components, namely: self-motivated, structure, order, persistence, alone/with peers, tutor-motivated and sound.

Students who perceived their personal study to be of high quality were self-and tutor-motivated, persistent (worked for lengthy periods at a time), liked structured activities, liked to organize themselves in a certain order, worked better alone and in quieter environments than their lower achieving peers.

(b) Objective Method

Univariate ANOVA reveals that four preferred personal study styles (‘Self-motivation’, ‘Alone/with Peers’, ‘Persistence’ and ‘Sound’) showed a significant difference (at 95%) between the three objective levels of achievement. Students in the high achievement category therefore like to be self-motivated, prefer quiet environments, dislike groupwork and prefer to work for significant periods at one time. Low performers, on the other hand, are less motivated, like to work with an accompanying soundtrack and enjoy groupwork activities.

Discussion and Conclusion

In common with the research on school students by Hong (2001) more distinguishing personal study style components resulted from the analysis of the three self perceived achievement groups than from the groups based on actual achievement. This is because the former group reflects not merely the marking system but the students’ efforts and attitudes to their work.

Hong (2001) comments that if the personal study environment is tailored to meet the individual preferences of learners “…it is reasonable to expect an improvement in homework attitudes and achievement similar to that attained when the in-school learning environment was matched to each student’s learning style.” Explicit self identification of preferred learning style might help the student as in other ways when such self reflective practices bear fruits.

In HE the personal study element has traditionally made up a high proportion or the learning strategy (remember the old cliché “you read for a degree rather than being taught it”). This contrasts greatly with student experiences at earlier stages of their educational career. Historically, while sterling attempts have been made to foster learning in the HE classroom, the out-of-class environment has always been approached in a rather ‘laissez-faire’ manner. It is suggested in this paper that if we accept learning environments are important factors in the learning process and we are intent on improving student achievement, then strategies should be developed to address the personal study environment. This is particularly vital in the context of increasing distance learning components in HE courses which could have a significant influence on the engagement and achievement of learners.

We propose that further research should concentrate on an examination of differences between subjects within Geography (e.g. physical and human) and perhaps investigate how factors vary across the years of study. We noted considerable within-achievement-level variation and suggest that the different environmental components could differentiate between subgroups based on other common characteristics rather than achievement (e.g. mature or young, male or female).

Finally, our research suggests that in HE, pedagogic researchers should be familiar with work on teaching and learning at all levels in education and we should not fall into the trap of assuming our learners do not have a long histories and well developed personal learning styles.

Above all, we need to alert our students to the importance of approaching their home studies in ways that will enhance their academic performance.