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  Aims: Effectiveness of human resources training depends on the quality of training. This study was carried out with the aim of identifying the components of quality in human resources training and proposing a new model of quality assurance in human resources training by using these components and the analytical system of Importance-Performance Analysis (IPA).

  Methods: This exploratory mixed method study was performed in 2011. Qualitative and quantitative data were collected by interviews and two questionnaires. 30 learners and 16 instructors were selected for interview by purposive sampling method and 94 learners and 21 instructors were selected by stratified random sampling method for filling the questionnaires. All samples were the instructors and learners of Iran Telecommunication Company training courses. Data were analyzed by qualitative statistical methods, Pearson correlation coefficient and paired T-test using SPSS 11.5 software.

  Results: 48 components of quality in human resources training were identified and an operational model was proposed for evaluation and quality assurance in human resources training based on these components and the IPA model analytical system.

Conclusion: The Importance-Performance Analysis (IPA) model is capable of evaluating and assuring quality in human resources training and can precisely identify the strengths and weaknesses of the educational system and provide guidance for strategy formulation in order to improve and assure the quality.

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Abstract
Introduction: Faculty development programs include all types of systematic support to improve faculty members as teachers, researchers, and citizens of universities, professions, and larger societies. Developing systematic and innovative faculty development programs is among the ways of improving the academic system. Due to the significance of such programs and their effective role in the quality of academic systems, it is essential for university managers to enhance the quality of such programs. Identifying and assessing the strengths of such programs can serve as an accelerator in setting guidelines for holding higher quality programs. For this reason, the present study was an attempt to identify the strengths of faculty development programs from the perspective of faculty members themselves, as the immediate stakeholders of the programs.
Methodology: Using semi-structured interviews in a qualitative and phenomenological design, 29 lecturers at Shahid Beheshti University were asked about their attitudes on the strengths of the faculty development programs. The transcribed interviews were coded using the Strauss and Corbin framework.
Results: Three strengths were identified for the programs: “prominent Lecturers”, “suitable topics and content” and “effective teaching-learning methods”.
Conclusion: Identification of only three strengths for faculty development programs  indicates that the mentioned programs lack the necessary quality and that fundamental revisions in policy-making, planning, and implementation are called for.

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Introduction: Knowledge Management maturity (KMM) determines the capacity and stages of the organizationchr('39')s growth in processes and the readiness and identify of the necessary element for the successful implementation of Knowledge Management strategies, goals and plans. This study was conducted with the aim of designing a model for assessing KMM in healthcare organizations.
Methods: This was an applied research that has been done by mixed method. At the qualitative phase, snowball sampling was used. Semi structured interview was done with 12 experts in healthcare organizations in Tehran. The interviews were analyzed by qualitative content analysis. For Reliability there were used two methods, reviewing articles after implementation by expert peoples and agreement of two coders. According to extracted factors, close questionnaire was prepared and distributed to 120 expert peoples by purposive sampling method and requested them to prioritize the choices according to Likert scale. For data analysis, SPSS 22 and exploratory factor analysis was used.
Results: In extracted model, five main layers were identified, including strategy, processes, Enablers, outcomes and external factors. The KMM levels include of initial, awareness defined, managed, optimized, entrepreneur and professional. The maximum load factor was related to the managed level (0.964). Each level of maturity was correlated with next level, indicating continuity of KMM levels (p<0.05).
Conclusions: The results showed in KMM and learning organizations the social dimension in healthcare service was more important than technical aspect as relates to the health of community and peoples. The role of knowledge culture and leadership in KMM and learning organization were more prominent than other factors.