Chemical educators have often assumed that success in solving mathematical problems should indicate mastery of a chemical concept. To this end, we have developed algorithms. However, Nurrenbern and Piekering ( 1 ) and Pickering (2) found little connection between solving an algorithmically-based problem and understanding the chemical concept behind that problem. Sawrey (3) further supported Nurrenbern and Pickering's findings.These studies quantitatively evaluated success in solving a conceptual problem versus a similar algorithmic problem. These studies found that many students could not use chemical concepts to solve conceptual problems.These findings were further supported by Nakhleh (4).Nakhleh found that across all levels of first-year chemistry students (from remedial to honors) conceptual problem-solving ability lagged far behind algorithmic problemsolving ability. She determined through the use of paired exam questions, that a sizable percentage (31% in that sample) of our firsbyear students are low conceptualhigh algorithmic students; students adept a t solving problems with algebraic equations, hut having only limited understanding of the chemistry behind their algorithmic manipulations.In the present study our objective was to ascertain what students do think about when they solve conceptual and algorithmic problems and to determine further if there are differences andlor preferences in their approach to each.We. therefore. used aired exam auestions on rras laws to select studentsfor interviews. In tke interviewwe probed their conce~tual understandinrr and their ~roblem solvine in detail. w e tried to determhe how the' students weni about solving a conceptual problem versus an algorithmic problem. We also endeavored to probe their preferences for solving either type of problem. MethodOur sample consisted of 60 freshmen chemistry students who were all enrolled in the same introductory course for declared chemistry majors. No other majors were represented in this sample. The professor for the course used a traditional problem-oriented lecture approach.This study was completed in two parts. The first part of the study used the paired questions technique to identify students as being either conceptual or algorithmic problem solvers. Two problems--one conceptual gas law problem and one algorithmic gas law problem-were placed on the third exam in the course where gas laws were being examined. Success or failure on these were recorded and students were grouped in one of four categories: High AleorithmiJHirrh Conce~tual (answerine both ~m b l e m s coFrectly,; ~i~t ~l~o r i t h m i r /~o w ~once&al (&swering the conceptual prohlem incorrectly J; Low AlgorithmiJHigh Conceptual (answering the algorithmic problem incorrwtlv); Low AleorithmidLow Conce~tual (answering neiProblem I.The following diagram represents a cross-sectional area of a rigid sealed steel tank filled with hydrogen gas at 20 ' C and 3 atm pressure. The dots represent the distribution of all the hydrogen molecules in the tank.Whlch of the follow...

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The authors' aim is to promote compliance with international legal standards by articulating intersections between young people's human rights and restorative justice principles — for legal theorists through transdisciplinary thinking and for practitioners by introducing the Rights Based Restorative Practice Evaluation ToolKit developed through this conceptual framework (Moore, 2008). This comprehensive approach was developed within the Canadian legal, social policy and youth justice contexts. Notwithstanding potential bias stemming from cultural or political milieu, the authors argue that rights-based restorative justice could contribute to the advancement of ethical practice in many UN-member states attempting to adopt these common frameworks.