’s Alpha has been calculated separately for each of the factors in addition to the whole data (see Table 3).

The three factors were also tested using the Kolmogorov-Smirnovin test and proved to be based on normal distribution data.

In the methodology, the critical value for Cronbach’s Alpha is considered to be above the 0.7 level. As the results of Table 3 show, all the items and variables turned out to be reliable in this study.

In addition, the correlations between the variables turned out to be suitable. Nearly all the correlations among the variables included in each of the three factors were between 0.2 and 0.6. These values fulfil the Tabanik-Fid- ell criteria for valid and reliable factor analysis. In addition, the correlations are not so high as to be at risk of multicollinearity.

The variables have been pre-tested and measured using an existing ordinal scale. The variables and items were also divided according to the normal distribution. The data did not contain any outliers or observations crucially distant from the rest of the data.

The traditional way of evaluating the reliability is the split-half method. In this case, a practical way of viewing the data was to analyse the data from the years 2010 and 2011 separately.

All the items of the factor analysis were crosschecked using the independent samples t-test. Only one item showed statistically significant difference, which is most probably only because of random variation while operating on the risk level p < 0.05 (The item was number 13, Organisational changes).

The factor analysis of the entire data (years 2010 and 2011) also produced very similar results to the 2011 data alone. All three factors (Role, Environment, Innovativeness) were loaded according to exactly the same schema and values. The items excluded were also nearly identical: in the original data the variables rejected were 12, 25, 26, and in the united data they were 4, 12, 26.

The results related to the age of the subjects were the most interesting. However, the distribution of the age groups was within a narrow range: under 22 years old, 23 to 30 years old and over 30 years old. The outcome related to age was so clear that it indicates that the older, in-service teachers should be the target audience of further study of the NEMP-model.

ANOVA-tests are not totally robust and immune to data that is not formed according to the normal distribution (Field, 2009: pp. 359-360, 559) . In the items in our data, positive answers dominated in some variables, causing the forms of distributions to be skewed to the left. To avoid any wrong, unreliable interpretations, the results produced by the ANOVA-tests have been double-checked using non-parametric tests (Clark-Carter, 2010) . As a replacement of the t-test, the Kolmogorov-Smirnov Z-test was utilised when evaluating the age group differences (Field, 2009: p. 548) . In addition, ANOVA-tests were filtered through the Jonckheere-Terpsta- test, because there was a presumption that the trends within the groups would grow systematically (Field, 2009: p. 568) . In summary, the non-parametric tests produced identical answers to the demanding matching methods of the original tests.

5. Discussion

How does the tool known as New Educational Models or Paradigms, originally developed for ICT-education research purposes, and here used in a modified version, fit for the research of Outdoor Education (OE) for the

Table 3. Cronbach’s alpha separately for all variables and the three factors of outdoor education (OE).

teacher professional development? The empirical results of this study support the theoretical part of the New Educational Models or Paradigms presented in the paper. The factor analysis and the other outcomes of the data confirm the design of the study. The entity certainly gives new evidence for the development of outdoor education.

The data was collected during two different autumns. This gave an opportunity to view the data according to the split-half method. Theoretically, for several reasons, there was no motivation to hold the presumption that the results would be different: 1) the students were selected for university using the same type of tests and examinations, 2) the official content of the course has remained the same and 3) the lecturer in charge of the outdoor education did not change. The empirical data supported the hypothesis. There was no difference between the results in the data collected in 2010 and 2011.

Even the items excluded from the factor analysis provide new thoughts for the further development of the NEMP theory. Items number 4 (“instruction tool”), 12 (“technological innovation”) and 26 (“Multi-disciplinary approaches”) were excluded from the factor analysis as reported in the Results chapter. These variables were left out of the factor analysis because they did not correlate with their own factor. Otherwise, the following items were eligible: variance was high enough, and the form (skewness: kurtosis) reached above average-level values. Items number 4 and 12 did not correlate with the variables they should have, and conversely, item 26 did correlate with practically all of the items. This is the mathematical and statistical explanation for excluding these three items.

What are the pedagogical benefits of using Outdoor Education (OE) applications in teaching biology at school? The items excluded from the factor analysis provide new thoughts for the further development of the NEMP theory. First of all, the fact that the item Multi-disciplinary approaches correlated with nearly all other items indicates that outdoor education is very integrative by nature. It combines several topics, such as biology, geography, geology and environmental education. Outdoor education also seems to have a very holistic nature; it captures the students’ imagination and engages them immediately in real action. There is no essential need for ‘instruction tool’, as represented by item 4. Outdoor education also takes place in nature, and the item technological innovation might sound irrelevant and out-of context.

The differences related to age and schoolwork experience gave certain indications. Teachers with more practical classroom experience clearly see more options to break routines by using the new alternatives and challenges offered by outdoor education. As was reported earlier in the Results section, these differences turned up especially in the context of the items Knowledge market place, Communication forum and Information bank. Those teachers with more experience, and perhaps also with more self-confidence, felt that outdoor education contains knowledge-based elements which do not exist in the classroom environment, in text books or in audiovisual or ICT-materials.

There was also a statistically significant difference related to age and work experience in regard to the items Outdoor education as provider of feedback and Outdoor education as tool. It seems that real work as a teacher gives more vision about how to apply outdoor education solutions.

6. Conclusions

The results strongly support the vision of utilising short-term PD-efforts (Lauer, Christopher, Firpo-Triplet, & Buchting, 2014) instead or side-by-side with long lasting courses (Guskey & Yoon, 2009) . The results of this study encourage the use of intervention type activities in teacher professional development.

The results contain clear hints that the study should be repeated among teachers in in-service training. This might provide new evidence for the practice of outdoor education and strengthen the methods of the NEMP approach that came out of this study, thus making it a reliable tool and valid theory.

In Finland, the new trend (National Board of Education, 2015) underlines interactive teaching environments and learning out of school as a resource for teaching. Learning should be multifaceted and combined to place and time. Besides the traditional subject orientated teaching the curricula give guidelines about how to use an approach called “phenomenon based learning”.

How does the role of Outdoor Education (OE) in teaching biology at school differ from the role of using traditional classroom applications? Environmental problems such as the loss of habitats and biodiversity, climate change and all the other environmental challenges will have to be faced by everyone today and in the future (Hanski, 2011; Harley, 2011) .

NOTES

*Corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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