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Background: The area of research aimed for a more efficient e-learning is slowly widening from purely technical to the areas of psychology, didactics and methodology. The question is whether the text or background color influence the efficiency of memory, i.e. learning. If the answer to that question is positive, then another question arises which combination of colors is more efficient, and which one may make the learning more difficult. This article presents results of a study on that subject. Purpose: The basic idea of the study is to examine whether there is a difference in memorizing text in study subjects of the experimental and control group if the only variable tested is a different combination of font color and background color. The study is divided into several phases. In the first phase, a selection of texts was made, in the second memory tests of the control group were performed, in the third, a selection was made of text and background colors, while in the fourth phase memory tests were conducted in the experimental group. Following the testing, data analyses were conducted by a single analyst. Setting: The testing was conducted between November 2006 and January 2007 (control group) and between November 2008 and January 2009 (experimental group) on the Teaching college of the University of Juraj Dobrila in Pula, Croatia. Study Sample: The testing was conducted 42 female and 2 male volunteer students of the first year of the Teaching college of the University of Juraj Dobrila in Pula, average age of the students was 19,4 years for control group and 24 female and two male volunteer students, average age was 19,4 years for experimental group. Intervention: The study is divided into several phases. In the first phase, a selection of texts was made, in the second memory tests of the control group were performed, in the third, a selection was made of text and background colors, while in the fourth phase memory tests were conducted in the experimental group. Research Design: Experimental; Control or Comparison Condition: Control group: Students were divided into four groups with 10-12 students in each group. Testing was conducted at the same time for all the four groups in the informatics/computer laboratory. The students were each time sitting on same seat and had similar conditions (as directed by the context). The testing was conducted in such a way that students read the text for 180 seconds from the monitor, then the monitor was turned off, and without delay they wrote down using pen and paper everything they could remember from the text they read. Test subjects were allowed to read the text as many times as they could, but were not allowed to make any notes. They were also allowed to quietly repeat the words, without interfering with other students' testing. Test subjects were told to write the text as literally as possible. Writing time was limited to 210 seconds. Following text writing, they were given a break of 300 seconds, after which they had another test. The students wrote 5 tests in a single day. Experimental group: Testing was conducted using the same parameters as the control group (same monitors, same texts with identical design, same computer laboratory, and students were positioned to look at the monitors from approximately same distance; the study was conducted in the same season, with same breaks etc.). The only difference was in combinations of text and background colors. Data Collection and Analysis: The number of acceptable tests used in the analyses varied between 32 and 43 in the control group. Some of the subjects did not attend certain tests, and some tests were excluded from the analyses due to the notes written by the students (headache, lack of sleep etc.), or due to the results that were judged to be a significant outlier compared to the rest of the group. Similar situation was present in the experimental group, with the number of accepted tests between 15 and 22 (with a total of 26 test subjects). Apart from the above mentioned reasons for exclusion, additional exclusion criterion in this group was weak concentration due to combination of text and background colors, which led to a somewhat higher number of excluded tests. Test number 22 had the same color combination for the control and the experimental group. The average results of this test show that in the experimental group students wrote 42.37% of the terms, while the control group wrote 42.20%. The average standard deviation for the control group was 7.94 while in the experimental group it was somewhat higher at 9.25. This is explained by two facts: a) tests in colors result in greater difference in achieved results; and b) deviation in a smaller group has greater influence on standard deviation. Table shows results of the tests based on text and background colors sorted from better to worse results. The results are sorted based on the black-on-white combination used in both groups. Since the results of the experimental group for that combination are slightly higher than the results in the control group, the relative difference was corrected and used. Result analysis has shown that there was a great difference, over 40% (from +17.64 to -26.58% in comparison to the black-on-white combination), in the percent of remembered terms in individual color combinations. Findings: Result analysis has shown that there was a great difference, over 40% (from +17.64 to -26.58% in comparison to the black-on-white combination), in the percent of remembered terms in individual color combinations. Conclusion: This study is part of a larger project, with the main goal to establish the elements of more efficient e-learning. On one hand, the control group used the standard color combination (black font on white background), while the experimental group used different color combinations of texts and backgrounds. The achieved results have shown which color combinations for font and background should be used to achieve better memorization effect. The difference in memorizing could be rather great, up to 40%, so the combination of font and background color should be taken into consideration in preparation of e-materials for e-learning. Citation: CARNet's Reference center -- Development of Educational Materials http://wwww.carnet.hr/referalni/obrazovni/ iom/ - (access 31.08.2009). Mateljan, V., Siranovic, Z., Simovic, V. Prjedlog modela za oblikovanje multimedjskih web nastavnih sadrzaja prema pedagoskoj praksi u Republici Hrvatskoj, Journal: Informatologia 42, 1 (38-44) (in Croatian), 2009. Shire - http://www.shire.net/learnwebdesign/nocss/fonts.htm (access 31.8.2009.) Weinman, L: The Browser-Safe Web Palette, http://www.lynda.com/resources/webpalette.aspx (access 31.08.2009.) Zarevski, P. Psihologija ucenja i pamcenja, Naklada slap, Jastrebarsko (in Croatian), 2001. Zufic, J. Kalpic, D. (2007a) More Efficient Learning on Web Courseware Systems? World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Quebec City, Canada, 2007. (pp 6707-6716). Zufic, J. Kalpic, D. (2007b) Design Workshop for use of WebCT in Education of Teachers, 29th International Conference on Information Technology Interfaces, Knowledge Discovery in Education and Business Cavtat, Dubrovnik, Croatia. (pp 393-39). (Contains 4 tables.) [This study was partially financed by Zagreb Bank d.d.

The article describes a research conducted on students at the University in Pula, by which was attempted to establish whether there is a relationship between exam success and a type of online teaching material from which a student learns. Students were subjected to psychological testing that measured factors of intelligence: verbal, non-verbal and math-logical. Four different teaching resources were prepared for the same educational material. First of those was adjusted for students with the strongest verbal abilities, second for students with the strongest math-logical abilities, third for the students with the strongest non-verbal factor of intelligence. Fourth teaching material was prepared in such a way as to equally represent all three factors of intelligence, for a mixed group of students. Students accessed the online educational material using web courseware tool Moodle. Tests were much better solved by students who had adjusted teaching materials than by students in the mixed group, or those in the control group. This article describes the intelligence tests that were used in the study, structure of the teaching materials and results. (Contains 4 tables.) [This paper was published in: Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2007 (pp. 6707-6716). Chesapeake, VA: AACE.]

Concept map is a graphical tool for representing knowledge. They have been used in many different areas, including education, knowledge management, business and intelligence. Constructing of concept maps manually can be a complex task; an unskilled person may encounter difficulties in determining and positioning concepts relevant to the problem area. An application that recommends concept candidates and their position in a concept map can significantly help the user in that situation. This paper gives an overview of different approaches to automatic and semi-automatic creation of concept maps from textual and non-textual sources. The concept map mining process is defined, and one method suitable for the creation of concept maps from unstructured textual sources in highly inflected languages such as the Croatian language is described in detail. Proposed method uses statistical and data mining techniques enriched with linguistic tools. With minor adjustments, that method can also be used for concept map mining from textual sources in other morphologically rich languages., Comment: ISSN 0957-4174