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دادهکاوی دانشجویان انصرافی دانشگاه پیام نور استان تهران به‌منظور افزایش نرخ ماندگاری دانشجو (جلوگیری از رویگردانی مشتری) | ||
| مدیریت سازمان‌های دولتی | ||
| مقاله 3، دوره 7، شماره 2 (پیاپی 26)، فروردین 1398، صفحه 47-58 اصل مقاله (1.31 M) | ||
| شناسه دیجیتال (DOI): 10.30473/ipom.2019.39792.3144 | ||
| نویسندگان | ||
| سید علی اکبر احمدی1؛ تورج خیراتی کازرونی* 2 | ||
| 1استاد گروه مدیریت دولتی، دانشگاه پیام نور، تهران، ایران. | ||
| 2کارشناسی ارشد گروه مدیریت فناوری اطلاعات، دانشگاه تهران، تهران، ایران. | ||
| چکیده | ||
| از چالش‌های پیش‌روی مؤسسات آموزشی بالأخص مؤسسات آموزش عالی غیرانتفاعی کسب درآمد جهت تحقق اهداف است اما انصراف دانشجو در نقطه مقابل قرار دارد. با شناسایی دانشجویان انصرافی میتوان با اتخاذ سیاست‌های پیشگیرانه و حمایتی از کاهش وجهه مؤسسه جلوگیری و امیدوار به جذب درآمد مورد انتظار شد. این تحقیق با استفاده از دادهکاوی اطلاعات دانشجویان انصرافی دانشگاه پیام نور استان تهران طی سال‌های 91 تا 94 قصد دارد دانشجویان در معرض خطر را شناسایی کند. داده‌ها از سامانه آموزش استخراج و از 20 صفت محتملی مؤثر در انصراف مدلی با دقت 92٪ شناسایی شد. در مدل مذکور 6 مشخصة مستقل (سن، گروه، مقطع و دورة تحصیلی، مشروطی و جنسیت) و یک مشخصه وابسته (سنوات) شناسایی و متعاقباً درجه اهمیت مشخصه‌های دخیل در انصراف و ارتباط آن‌ها با یکدیگر تعیین شد. احتمال خطر انصراف (ریسک ریزش) اولویت‌بندی و جدول خطر احتمال برای ترم‌های مختلف ارائه شد. یافته‌ها حکایت از شناسایی سن به‌عنوان مهم‌ترین عامل دارد. از نظر سنی در کارشناسی دستة سنی 21-18 در ارشد 26-22 و در دکتری 31-29 پرخطرترین گروه‌ها هستند. از لحاظ دورة تحصیلی در کارشناسی و دکتری دورة رسمی و در ارشد دورة آموزشی پژوهشی رسمی پرخطرترین دوره می‌باشند. نرخ انصراف برای دانشجویان 19 و 20 سال در ترم سوم تقریباً 50 درصد است. | ||
| کلیدواژه‌ها | ||
| انصراف دانشجو؛ حفظ دانشجو؛ رویگردانی مشتری؛ شبکة بیزین؛ پاسخ خود یادگیرنده | ||
| عنوان مقاله [English] | ||
| Data mining withdrawal of the students of Payme Noor University in Tehran state to increase student retention rate (Preventing customer rejection) | ||
| نویسندگان [English] | ||
| Saied Ali Akbar Ahmadi1؛ Toraj Khairatikazerooni2 | ||
| 1Professor of Department of Management, Payame Noor University, Tehran, Iran. | ||
| 2. Ph.D of Department of Information Technology Management, Tehran of University, Tehran, Iran. | ||
| چکیده [English] | ||
| The challenges facing educational institutions, especially nonprofit higher education institutions, are to earn money to meet their goals. Student withdrawal is in the opposite direction. By identifying students as opt-outs, preventive and supportive policies can be anticipated to prevent a reduction in the image and hopes to attract revenues. This research is aimed at identifying students at risk by using the Data Mining Data of the Student attention Center of Payame Noor University of Tehran during the years 91-94. Data were extracted from the education system. Of the 20 potentially effective attributes, a 92% accuracy model was identified. In the model, six independent characteristics (age, group, grade, probation, and gender) and an associated attribute (term) were identified and subsequently the degree of importance of the attributes involved in the withdrawal and their relationship with each other was determined. Risk of withdrawal (risk of attention) and risk ranking table for different terms were presented. Findings indicate that age is the most important factor. From a Sunni point of view, the bachelor degree is between the ages of 21-18 in the senior age group of 26-22 and the PhDs 31 to 29 in the most risky groups. In terms of academic and postgraduate degrees, they are the most risky period in the formal and continuing education programs of the research course. attention rates for students aged 19 and 20 are about 50% in the third semester. | ||
| کلیدواژه‌ها [English] | ||
| student withdraws, retention students, prevent customer churn, Baizian network, self-learner's response algorithms | ||
| مراجع | ||
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