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Targeting Functions: A New Approach to Anti-Smoking PSAsSaunders, Paige F. 08 September 2011 (has links)
No description available.
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The Effects Of Problem Solving On The Topic Of Functions On Problem Solving Performance, Attitude Toward Problem Solving And MathematicsEge Ozalkan, Bilgen 01 May 2010 (has links) (PDF)
The purpose of the study was to investigate the effect of Problem Solving Method on 9th grade students& / #8223 / problem solving performance and attitudes toward mathematics and problem solving. This study was done in 2007-2008 academic year, in a private high school in Ankara. In the present study the experimental-control group pre-test post-test research design was used.
The study was done with 67 students of the private high school. Experimental group was instructed with Problem Solving Method and control group was instructed with Traditional Method. The treatment was given for seven weeks, 21 lesson hours.
Problem Solving Performance Test, Problem Solving Attitude Scale and Mathematics Attitude Scale were administered as a pre test and a post test.
Independent samples t-test was used to examine the hypotheses of the present study. The results revealed that there were no statistically significant mean differences between experimental group and control group related to gained scores of understanding the problem, making a plan and carrying out the plan steps in Problem Solving Performance Test and Mathematics Attitude Scale. However, there was a statistically mean difference between these groups with respect to gained scores of Problem Solving Attitude Scale.
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Adoption of Disruptive Technologies : Exploratory research into consumer attitude formation regarding Bitcoin adoptionSaénger, Jonathan, Marcus, Sahlin, Chris, Uhler January 2021 (has links)
Attitudes are based on motivations and are formed in anticipation that the person will handle similar information at a later date. Attitudes are, therefore, necessary collections of pre-determined behavioral intents toward certain information (Solomon et al., 2016). Attitudes and their underlying functions form using a hierarchical structure where certain elements hold the primacy of effect over the remainder. These elements affect, behavior, and cognition as presented by Solomon and colleagues (Solomon et al., 2016). This study aims to explore how investors form attitudes towards the adoption of unfamiliar attitude objects, specifically when confronted with communications regarding Bitcoin adoption. The reason for this study is threefold; firstly, congruent academia has only conducted temperature checks on already established attitudes towards Bitcoin from diverse crowds in a spread of non-western cultures (Gagarina et al., 2019; Anser et al., 2020). Secondly, the aforementioned studies incorporated loosely defined sample groups. Understanding technology adoption, following the theories of Rogers (1995), requires that inaugural research is done on those who are most likely to adopt the technology. Lastly, congruent research has yet to tackle attitude formation on Bitcoin as an asset. Established research all commit to researching already established attitudes on a less niched sample (Gagarina et al., 2019; Yoo et al., 2020). The conclusion of said studies found thematic, contextual antecedents to why certain participants had certain attitudes. However, these studies do not explore the underlying hierarchy or function of said attitudes. To fill such a gap, a study following a deductive, exploratory nature was developed. Through thematic coding of qualitative interviews, this study contributes to the existing literature in two aspects: first, active Swedish investors rely on affective reasoning when faced with this particular unfamiliar attitude object. Second, such affective reasoning is most likely a result of participants defaulting to the grouping of information within the knowledge function, as no cognitive baseline (in the form of understanding price developments in Bitcoin) could be established. The general attitude formation followed an affective dominant, low-involvement hierarchy created through the knowledge function.
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