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 Discussion, Conclusion & Suggestions

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The Effect of Reading Comprehension and Problem So (1)

4. Discussion, Conclusion & Suggestions 
In this study, answers were sought for “Are the reading comprehension skills (reading rate, reading accuracy percentage, 
prosodic reading, literal comprehension, inferential comprehension) effective on classifying students with high and low 

Journal of Education and Training Studies Vol. 5, No. 6; June 2017 
problem solving success?” and “What is the relative order of importance of problem solving strategies in classifying 
students with high and low problem solving success?” 
In terms of the first problem of the research, the power of reading comprehension skills in predicting students with high 
and low problem solving success was analysed and it was determined that fluent reading skills (reading rate, word 
recognition rate, prosodic reading level) weren’t effective in classifying students with high and low problem solving 
success. It was found in the studies of Jenkins and Jewell (1993), Tuohimaaa, Aunola and Nurmi (2007), Baştuğ and 
Keskin (2012), Başaran (2013), Yıldız (2013) that there is relation between fluent reading and comprehension of primary 
students. In this context, the fact that fluent reading skills aren’t effective on classifying students with high and low 
problem solving skills enabled us to see that fluent reading skills don’t affect problem solving skills directly; however, 
since fluent reading skills affect comprehension skills, they may affect problem solving skills indirectly. Further studies 
are required to determine this case. 
The effect of comprehension skills (literal comprehension, inferential comprehension) in classifying students with high 
and low problem solving success was researched. As a result of logistic regression analysis, it was seen that chi-square 
value obtained in the initial model decreased almost 100 points when comprehension skills entered the model and this fall 
was significant. Another result obtained in the research was that comprehension skills explained of the variance 30% 
(Cox&Snell R
=.301) and 40% (Nagelkerke R
=.402) in classifying students with high and low problem solving success. 
The fact that accurate classifying percentage in the initial model 54% rose to 77% when comprehension skills entered the 
model enabled us to see that comprehension skills had an effect in classifying students with high and low problem 
solving success. No quantitative study was found about the effect of reading comprehension skills in classifying 
students with high and low problem solving success. In the studies by Polat and Keşan (2013), Grimm (2008), Tuohimaa 
et al. (2007), Plomin and Kovas (2005), a relation was found between reading comprehension skills and problem 
solving skills at medium level. Hegarty et al. (1992) revealed that students with high problem solving success spend most 
of their time for understanding and planning while students with low problem solving success spend most of their time for 
doing calculation. The research results carried the results of these studies one step further and revealed that 
comprehension skills have a direct effect in classifying students with high and low problem solving success. 
The research results also revealed that one unit change in in-dept comprehension skill leads to 56.8% increase in low 
success odds while one unit change in literal comprehension variable leads to 36.3% increase in low success odds. This 
reveals that in-dept comprehension skill is more effective than literal comprehension skill in classifying students with 
high and low problem solving success. However, according to Kintsch (1988) literal comprehension lets us find answers 
for WH-questions (e.g. who, what, where, when, how) in the text. It is stated that the main purpose in reading a text is 
thought to be inferential comprehension but literal comprehension is a prerequisite for inferential comprehension to occur 
(Allen, 1985; Kinsch, 1988; Suk, 1997; Vacca et al. 2006). 
The reason for the fact that inferential comprehension is more effective on classifying students with high and low problem 
solving skill is that, as Kispal (2008), Chikalanga (1992), Zwiers (2004), Presley (2000) and Kintsch (1988) stated, an 
individual who made an inference during reading comprehension was at the same time reasoning. The role of reasoning 
during problem solving was defined as reaching a solution by integrating every proposition in the problem text in a logical 
consistency (Leighton and Sternberg, 2004). With reference to the definitions above, significant resemblances are seen 
between inferential comprehension during reading comprehension and reasoning skill during problem solving. 
Background information should be activated other information should be reached with reference to the explicit 
information in the text both in inferential comprehension during reading comprehension and in reasoning during problem 
solving. Literature shows that a positive relation exists between problem solving and reasoning skills (Barbey and 
Barsalou, 2009; Çelik and Özdemir, 2011; Çetin and Ertekin, 2011; Umay, 2003; Yurt and Sünbül, 2014). In the studies 
conducted by Panasuk and Beyranevand (2010), Moreno and Mayer (1999), Hegarty, Mayer and Mog (1995) it was seen 
that students with action-based interpretation (inferential comprehension) were more successful than those with 
word-based interpretation (literal comprehension It was seen that students with higher success spent 67% of their time 
interpreting sentences and 33% analyzing the numbers while students with lower success spend 43% of their time 
interpreting words and 57% analyzing the numbers. Sentence-focused solutions (inferential comprehension) were more 
effective than number and word-focused (literal comprensionn) solutions (Verschaffel and DeCorte, 1993). In the studies 
of Anderson (2010), Grimm (2008), Jordon, Hanish and Kaplan (2003), it was seen that reading comprehension skills 
increase their effects on problem solving success over the years. On the other hand, Jeanne stated that there is a critical age 
threshold in acquiring inferential comprehension skill and if not acquired at early ages, it becomes harder to acquire 
inferential comprehension skill at advanced ages. In this context, it is thought that inferential comprehension which is the 
variable that affects problem solving skill directly most is supposed to be developed at early ages. 
Within the context of the second problem of the research, the effect of problem solving strategies in classifying students 
with high and low problem solving success was analysed. As a result of the research, it was seen that problem solving 

Journal of Education and Training Studies Vol. 5, No. 6; June 2017 
strategies could classify students with high and low problem solving success with 88% accuracy. This rate is higher than 
the accurate classifying rate obtained in comprehension skills. In a study by Ulu (2011), problem solving strategy 
education was found more effective than reading comprehension strategy education. Both the results of this study and the 
findings in the study by Ulu (2011) may reveal that problem solving strategies are more effective than comprehension 
skills in increasing problem solving success because they allow reaching the solution directly, but understanding the 
problem is required to develop suitable strategy for the problem (Mayer, 1985; Artzt and Thomas, 1992; Hong, 1995; 
Morales, 1998; Goos, Galbraith and Renshaw, 2000). In this context, it can be said that comprehension is the 
prerequisite for developing a strategy.
It was concluded that the strategies with the most contribution to classifying students with high and low problem 
solving success are estimation and control, systematic listing, looking for a pattern and drawing figures and diagrams 
respectively and the effect of backward studying strategy is low. It was seen in the studies by Ulu (2011), Altun, 
Memnun and Yazgan (2007), Altun and Arslan (2006) that after the strategy education, problem solving success of 
elementary school students increased as they started to use estimation and control, systematic listing, drawing figures 
and diagrams, simplifying the problem, backward studying and looking for a pattern strategies. The findings in these 
studies show similarities with the findings of this study. In this study, problem simplifying strategy wasn’t used by the 
students but except for backward studying strategy, it was seen that the likelihood of other strategies being in the group 
with high problem solving success increases. Both the findings of this study and related studies reveal the necessity of 
problem solving strategy education for development of problem solving success.
Another important finding of this study is that the highest correlation through discriminat function is shown by strategy of 
writing mathematical sentence, but the relation is negative. With reference to this finding, as the rate of use of strategy 
of writing mathematical sentence increases, the likelihood of its being in the group with low problem solving success 
increases. The fact that strategy of writing mathematical sentence is almost half of the strategies used in the group with 
low success, as well as the fact that the rate of use of this strategy in the group with high success is less than the group with 
low success, confirms this finding. According to Baykul, this strategy is defined as determining the operations required 
and constructing equations or inequations for solution. It was determined in the studies by Pape (2004), Ulu (2011), 
Verschaffel and DeCorte, (1993), Hong (1993/1995) that students with low problem solving success directly construct 
equations or inequations for solution without planning (strategy choice) or directly start operations and that the operations 
they choose are mostly irrelevant. Koedinger and Tabahneck (1994) found that when strategy is changed during solution, 
reaching a solution becomes easier, whereas Kaur (1998) found that strategy knowledge of unsuccessful students is 
inadequate and they can’t choose suitable strategy for solution. In this context, students with low problem solving 
success should be made aware that there are other strategies than strategy of writing mathematical sentence and they 
should be equipped with these strategies because according to Montague (2005), when students are given strategies and 
a process to make mathematical problem solving less complicated, then they could learn those strategies and become 
successful problem solvers. Also students who have experienced little success in mathematics can learn various 
problem-solving strategies that will help develop mathematical skills and build confidence in their own abilities as 
problem solvers (Pajares,1996).
Accordingly, it is concluded that students with low problem solving success should focus more on inferential 
comprehension skill of reading comprehension skills, followed by superficial comprehension skill. In this context, in 
their problem solving practices, teachers are suggested to start with inferential comprehension and literal 
comprehension drills to increase the success of students with low problem solving success. Reading comprehension 
skills weren’t effective in this study in classifying students with high and low problem solving skills, but further studies 
are required to determine whether these skills affect problem solving success through comprehension skills. It is seen 
that in terms of strategy, the most important reason for a student to be in the group with low problem solving success is 
that s/he uses strategy of writing mathematical sentence. In this context, strategy education for students with low 
success should be focused on.

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