Section 1 : Advanced Monitoring and Evaluation Course

 		Lecture 1 Introduction 0:53
Lecture 2 Course Project 1:53
Lecture 3 Meaning of project and Project Management 2:29
Lecture 4 Key characteristics of a project 2:45
Lecture 5 Position of Monitoring and Evaluation in project management cycle 2:41
Lecture 6 What is monitoring 2:36
Lecture 7 Types of Monitoring 3:40
Lecture 8 What is Evaluation
Lecture 9 Types of Evaluation 5:42
Lecture 10 Evaluation Criteria 5:18
Lecture 11 Objectives of Monitoring and Evaluation 2:44
Lecture 12 Differences between Monitoring and Evaluation 3:45
Lecture 13 Components of Monitoring and Evaluation systems 2:13
Lecture 14 Meaning of monitoring and Evaluation system 1:32
Lecture 15 Who should be involved in M&E activities
Lecture 16 Introduction to result chain 2:5
Lecture 17 Result chain in details 7:56
Lecture 18 What is logical framework 1:32
Lecture 19 Description of Logical Framework 2:52
Lecture 20 Indicators
Lecture 21 Means of verification 2:46
Lecture 22 Risks and Assumptions 2:24
Lecture 23 How Assumptions work in Log-frame 1:40
Lecture 24 Background to logical framework 2:44
Lecture 25 Designing logical Framework
Lecture 26 Designing logical Framework Sample two 9:19
Lecture 27 When do we use logical Framework 0:0
Lecture 28 SMART Indicators 3:44
Lecture 29 Introduction to M&E Framework 1:46
Lecture 30 Structure and Format of M&E Framework 3:2
Lecture 31 M&E Framework sample 5:39
Lecture 32 Introduction to M&E Methods 2:11
Lecture 33 Direct Observation 3:41
Lecture 34 Surveys or interviews 2:51
Lecture 35 Focus group discussions 2:48
Lecture 36 Pile-ranking exercise 2:42
Lecture 37 Data triangulation 2:48
Lecture 38 Introduction to M&E Tools 4:14
Lecture 39 Data Types 3:6
Lecture 40 What influences tools choice
Lecture 41 Questionnaire 3:22
Lecture 42 Designing Questionnaire 6:17
Lecture 43 Tips on questionnaire designing 3:33
Lecture 44 Practical questionnaire designing 9:44
Lecture 45 Focus group discussion guide 4:54
Lecture 46 Practical Focus group discussion guide designing 5:10
Lecture 47 Key Informant Interview Guide 3:0
Lecture 48 Practical Key Informant interview Guide formulation 4:4
Lecture 49 Observation checklist 2:0
Lecture 50 Sample Observation checklist 3:36
Lecture 51 Beneficiary sign in sheet 3:0
Lecture 52 Sample sign in sheet 2:50
Lecture 53 Introduction to sampling 4:5
Lecture 54 Representative random sampling 6:8
Lecture 55 Purposive sampling 3:10
Lecture 56 Introduction to research ethics and informed consent 3:13
Lecture 57 Obtaining informed consent from respondents or beneficiaries 3:35
Lecture 58 Research Misconduct in M&E 3:40
Lecture 59 Causes of poor data quality 3:28
Lecture 60 Monitoring data quality during collection process 3:2
Lecture 61 Introduction to data Analysis 2:42
Lecture 62 Quantitative data analysis 1:41
Lecture 63 Using Mean, Frequency, Percentage, Range and Standard deviation 11:5
Lecture 64 Bar charts 6:11
Lecture 65 Stacked bar chart 3:50
Lecture 66 Pie Chart 3:16
Lecture 67 Line graph 2:46
Lecture 68 Scatter plot 1:57
Lecture 69 Cross tabulation 2:20
Lecture 70 Qualitative data analysis 16:3