Online learning has been growing rapidly in recent years providing increased opportunities for tertiary institutes to reach out to learners who previously may have had limited access to a traditional university. Although students frequently use information technologies in their daily life online learning requires considerably more competencies than basic computer skills. Many students are unsuccessful in their learning without face-to-face contact and collaboration with lecturers and peers. They can feel isolated and doubt their ability to succeed in the online course. To increase online learner success support is needed especially to improve learner self-efficacy. Very few studies have focused on student self-efficacy in an online learning environment and especially those conducted in an authentic setting. Learner control is thought to facilitate students in online learning but the relationship between learner control and learner self-efficacy is still unclear. Therefore this study intends to examine this relationship using an embedded-correlational mixed method design to answer the research question what is the relationship between learner control and online learning self-efficacy? The quantitative approach was used to find the correlations among learner control online learning self-efficacy and related variables such as age gender prior online experience and computer skills. An online Learning Self-efficacy Scale (OLSES) was constructed and validated with an internal consistency of 0.895. Open-ended questions were added to the questionnaire to gain a greater level of insight of online learning experience in relation to self-efficacy and learner control. Seventy-five students in a four year teaching online programme at a New Zealand tertiary institute participated in the online survey. Data analyses revealed that the relationship between learner control and online learning self-efficacy was confirmed r = .526 p < .01. Age and gender had no effect on the relationship while prior online experience computer skills for social and academic purposes did. The multiple linear regression showed that learner control and computer skills for academic purpose are good predictors of online learning self-efficacy. Analyses of the qualitative data not only confirmed the quantitative findings but also provided insight into the nature of self-efficacy and importance of feedback in the online setting. As a result of this study the embedded framework for successful line learners (SUCCESS) was developed and is recommended as a set of guidelines for online learning developers.

Resource leveling schedule is important for construction planning process very much because quantity of resource such as labors is limited. The optimal solution to allocate enough resource for every activity is main principle for project successful. But in ordinary they always observe that have different quantity of resource every time periods is called of “Resource fluctuation”. So planners have to adjust first schedule is called of “Resource Leveling”. This method necessary for decrease resource fluctuations or make uniformly resource demand level . However normal method (heuristic method) to solve this problem is difficult and use much time. So in present there is new developed method by create model in spreadsheet computer programs such as Microsoft Excel. This new method can solve very complex resource leveling problem well..So in this research if we add vary relationship options such as SS (Start-To-Start) FF (Finish-To- Finish) or NO (No Relation) for activity in model objective is increasing optimal solution flexibly and output solution is better than El Rayes & Jun ‘s Model. We can discover for optimal solution from this new model that received uniformly resource demand level of project schedule in the end

The objectives of this research are to analyze the relationship between securities price and the efficiency of the account receivable management and to study the model of improving the efficiency of the account receivable management of the agricultural business group in the Stock Exchange of Thailand. The number of data which had been used in this research was 16 random companies of all 22 companies from the listed companies in the Stock Exchange of Thailand agricultural business group by using purposive sampling method. The researcher used both quantitative and descriptive analysis method by bringing the quantitative data analysis from 2006-2010 to descriptive analyzing which had compared between the selling revenue account receivable value allowance for doubtful bad debt account receivable turnover average collection period book value per share primary earnings per share and securities price. The results of analyzing are changing in the account receivable of Chiangmai Frozen Foods Pcl. Lee Pattana Pcl.; changing in the bad debt of Pak Food Pcl.; changing in the average collection period of Thai Rubber Latex Corporation (Thailand) Pcl. Pak Food Pcl.; changing in the book value per share of Pak Food Pcl. Kiang Huat Sea Gull Trading Frozen Food Asian Seafoods Pcl. Asian Seafoods Pcl.; changing in the primary earnings per share of Thai Rubber Latex Corporation (Thailand) Pcl. Thai Luxe Enterprise Pcl. Lee Pattana Pcl. and Kiang Huat Sea Gull Trading Frozen Food Asian Seafoods had related to securities price per share.

This research were to study learning behavior and the relationship between learning behavior and academic achievement of students in taxation. The samples were students who studying management at the faculty of Business Administration and Liberal Art at RMUTL-Nan. The instruments for collecting data were behavior observation and tests. The statistical methods for analyzing data were mean and Pearson Product-Moment Correlation Coefficient. The results showed that the students’ learning behavior in taxation was at good level but the average achievement was moderate score: 63.81 out of 100 scores (C). The students’ learning behavior of five domains found that the intention of punctuality timely attention responsibility and attendance were good. Their understanding behavior was moderate. There was positive statistically significant relationship between learning behaviors and academic achievement of students in taxation at 0.01 levels. The correlation coefficient was 0.703.The learning behaviors could predict the academic achievement as 49.40 percent.

One important factor that makes the variations of electric current produced from solar cells (Ipv) is the variability of the weather conditions of the day. The one year experiment from January to December 2012 had been set up. The experiment of the comparison of the weather data satellite images and the different current (Ipv_d) was obtained from daily Ipv. The results illustrated that there were 4 major types of the relationship between the Ipv_d and weather conditions; 1) Low Ipv_d at around 2000 mA with low perturbations would correspond to the clear sky condition. 2) Perturbation of Ipv_d in some periods would correspond to the cloudy condition. 3) High perturbations of Ipv_d for all day long would relate to the rainy – cloudy condition. 4) High Ipv_d at around 4000 mA with low perturbations would relate to the cloudy condition all day long.