IFPRI, NEW DELHI
Impact of Capacity Building Under NAIP
6-7 June 2014
NASC Complex, New Delhi
Outline
• Background and Objectives
• Typology and Profiling
– Budget and Scope; Participating Institutions; Spread of Trainees by SMDs, Themes and Sub-themes; Trainees Profile; Destination Mapping and Top
Mentors /Facilitators
• Impact Assessment
– International Training - Attitudinal Changes; Benefits in terms of publications, technology, IPRs, Proposals, New Projects etc.;
– Cost and Benefits – Some case studies
– National Training – Some reflections
– Leadership Management Program – Utility and follow-up
• Conditions for Success of Capacity Building Programmes
• Suggestions and Way Forward
2
Background, Objectives and Framework
3
Background
• ICAR continuous to invest in capacity building (CBPs)
in frontier areas
• CBPs in deficit/frontier areas of contemporary
relevance and anticipated future
• Some flagship programmes:
Summer & Winter schools (SWSs))
Centre of Advanced Faculty Training (CAFTs)
Externally Aided Projects (like AHRD, NATP, NAIP, etc.)
11th Plan - ICAR sponsored 588 SWSs and CAFTs benefitting about 11000 scientists and faculty of NARS
Capacity Building Program under NAIP
• NAIP (launched 2006) - Contributes to the sustainable
transformation of agricultural research system
• NAIP has 4 components; and a part of first component
focuses on human resource development
• Overall objective of CBP was to enhance technical
capacity of NARS:
Predetermined 27 frontier areas of agricultural sciences in
advanced labs all across the world
Key objectives of the study
• Describe typology of CBP, trace input allocation, investments and outputs of thematic and research skills developed
• Document costs, benefits, productivity and efficiency gains of CBP
• Undertake a few case studies to assess potential of technological innovation as a result of CBP
• Document evidence of collaborative research programs and networks developed as a result of CBPs
• Document conditions for success of CBP and the way forward
Framework for Impact assessment
7
STEP 1: BENEFICIARIES OF THE PROGRAMS
Direct beneficiaries Indirect beneficiaries
STEP 2: OUTPUTS FROM THE
TRAINING PROGRAMS
STEP 3: OUTCOMES FROM
THE TRAINING PROGRAMS
8
Survey Group Sample Responses
Received
1. International Training
participants
337 178
2. Control Group (non-trained
scientists)
500 164
3. Heads of the
institutes/universities
90 12
4. National Training participants 600 30
Framework for Impact assessment contd..
Typology of Capacity Building Program
9
Highlights – Budget and Scope
10
91.33crores
L&CB
487
Trainees
7.86 Lacs
per Trainee
23
Countries
122
Institutions
6
Core Themes
27
Sub-Themes
38.26 crores (42%)
International Training
94%12 weeks Training
6%2-3 Weeks
Training
Distribution of Training Duration
Basic Sciences
Processing Technology
Biosecurity
Climate Change
Informatics
Social Science and Policy
11
122
Total Institutes
75%
ICAR Inst.
25%
SAUs
7%
Trainees From IARI
19%
Trainees
81%
Trainees
Top SAUs Participated3% UAS, Raichur
3% TN Vet and AS University, Chennai
2% PAU, Ludhiana
2% CSK , Palampur
Participating Institutions
Spread of Trainees by Subject Matter Divisions
12
Social-Sc
Engg
NRM
Fish
Animal-Sc
Crop-Sc
Hort
6%
8%
10%
14%
19%
20%
23%
SMD Horticulture Biggest Gainer followed by Crop Sciences
Trainees Profile: Designation (%) and Age / Experience (years)
13
Scientists / Asst. Prof.
24
Sr. Scientists / Assoc. Prof.
63
Principal Scientists /
Prof. 13
Age - 41 Exp. - 13
Senior Scientists a Major Lot
Age - 36 Exp. - 8
Age - 46 Exp. - 19
Female, 19%
Male, 81%
Female, 19%
Male, 81%
Female, 22%
Male, 78%
14
Gender of Trainees
All Trainees
ICAR SAUs
USA + Canada (70 + 3)
UK+ EU (8+9)
AU+NZ (4)
SEA (4)
EU – UK, Germany, France, Italy, Sweden, DenmarkSEA – Singapore, Malaysia, Thailand, PhilippinesOthers – Syria, Peru , Columbia, Mexico, Chile
Destination Mapping : Distribution of Trainees (%) : Countries & Institutions
16
Basic Sciences 48
Processing Technology
18
Biosecurity 10
Climate Change 8
Informatics 8
Social Science and Policy
8
Distribution of Trainees (%) by Core Theme Areas
17
Marker Asst. Selection 19
Carbon Trading 7
Bioinformatics 5
Nutraceuticals 5
Allele Mining 5
Biomolecules 5IPR 5
Fermentation Tech 4
Nanotech 4
Sensor Based Apps 4
Other Sub-Theme Areas
37
Distribution of Trainees (%) by Sub-Theme Areas
18
Our Top Mentors /Facilitators
Impact Assessment
–Trainees’ Perception
19
Trainees’ Perception about training program
20
•Training objectives met (92%)
•Training very comprehensive (82%)
• Training content directly relevant to area of work (82%)
Impact on skill development - research, communication and linkage & network
Research/ Technical
• Inspired new research ideas (94%)
• Learnt, which is immediately applied to current work 80%)
Presentation/Writing
• Improved presentation/writing skills (65%)
Linkage & network
•Develop linkages at universities/ institutes visited (33%)
Impact on attitudinal change
Motivational Change
• More motivated to do their job (83%)
Confidence Building
• More confident in their position (86%)
Expectations at work place
• Increased expectations from trainee, at work (85%).
Impact on Trainees’ level-productivity, efficiency and effectiveness
23
Efficiency
• More efficient at work (86%)
Productivity
• Increase in productivity (86%)
Effectiveness
• Increase ineffectiveness of trainees in their current organisation (86%)
24
Impact Assessment
– Trainees’ level
Indicators of benefits/outcomes of CBPs in terms of output index in pre and post training period
Note:-Technologies developed are defined application of techniques for improving productivity through
developing new varieties/breed. Possible technologies are:- prototype, genetic/stock, variety/breed, product,
vaccine, diagnostic kit, process, methodology/technique.
100 100 100 100 100 100 100 100 100
162
136 135 133
117113
109 107 107
0
20
40
60
80
100
120
140
160
180
ProjectProposals
submitted tonon-ICAR
Journalarticles
accepted forpublication
Patentssubmitted
ProjectProposalssubmitted
Journalarticles
accepted forpublication asa first author
ProjectProposals
submitted toICAR
Technologiesdeveloped as
a CO-PI
Technologiesdeveloped as
a PI
Technologiesdeveloped asa PI & CO-PI
Index pre training Index post training
Outputs Post-training incremental gains in output(%)
Journal articles • Bio-security/conservation (50%)
• Informatics (77%)
• Processing technology (45%)
• Basic Sciences (34%)
Technologies developed • Bio -security/conservation (6%)
• Processing technology (15%)
• Basic Sciences (4%)
Patent submitted • Processing technology (5%)
• Basic sciences(12%)
Project proposals submitted • Basic Sciences (13%)
• Informatics (33%)
Message: Biosecurity/conservation, Basic sciences, Processing
Technology & Informatics have gained more
Theme-wise benefits: publications, project proposals, technological innovations & patents submitted……….cont….
Outputs Post –training incrementalgains in output (%)
Journal articles • USA (32%)
• Others (48%)
Technologies developed
• Others (7%)
• USA (9%)
Patent submitted • Netherlands (100%)
• USA (75%)
Project proposals submitted
• Netherlands (50%)
• USA (23%)
Message: Training-location – Trainees trained at USAhave gained more with respect to outputs
Training Location –wise analysis of benefits: publications, project
proposals, technological innovations & patents submitted……….contd.
Outputs Post-training incremental gains in output(%)
Journal articles • Horticulture (68%)
• Fisheries (12%)
• NRM (33%)
Technologies developed
• Crop Sciences (24%)
• Horticulture (33%)
• NRM (32%)
• Fisheries (24%)
• Animal Sciences (5%)
Patent Submitted • Agricultural Engineering (30%)
Project Proposals submitted• Crop Sciences(68%)
• Horticulture (2%)
Message: Horticulture, Crop Sciences and NRM
Management have more gains with respect to outputs
Division analysis of benefits: publications, organizing events, project proposals, technological innovations & patents submitted……….contd.
Outputs Post –training incrementalgains in output(%)
Journal articles • Scientist/Assistant professor (51%)
• Senior scientist/Associate professor (26%)
Technologies developed
• Scientist/Assistant professor (32%)
• Senior scientist/Associate professor (56%)
Patent submitted • Senior Scientist/Assistant professor (80%)
• Principal scientist/professor (22%)
Project Proposalssubmitted
• Senior scientist/Associate professor (10%)
• Principal scientist/professor (23%)
• Senior scientist/Associate Professor have gained more with respect to journal articles accepted forpublication, followed by technologies developed, patent and project proposal submitted.
• Principal scientist/Professor have gained more with respect to patent and project proposalssubmitted.
Designation –wise analysis of benefits: publications, project
proposals, technological innovations & patents submitted……….contd.
Outputs Post –training incremental
gains in output(%)
Journal articles • 12 weeks (41%)
Technologiesdeveloped
• <12 weeks (15%)
Patent submitted • 12 weeks(42%)
Project proposals submitted
• 12 weeks(24%)
Message: Duration- Trainees underwent training for 12weeks (3 months) had more gains with respect to outputs.
Duration –wise analysis of benefits: publications, project proposals, technological innovations & patents submitted……….contd.
Outputs Post- training incremental
gains in output(%)
Journal articles • 35-40years (43%)
Technologies developed • <35 years(52%)
• 35-40 years(31%)
Patent submitted • 40-45 years(91%)
Project Proposals submitted • 40-45years(46%)
Message:
• Trainees with age of < 35 years and 35-40 years had gained with respect to
journal articles accepted for publication and technologies developed.
• Those of >40 years had gained more with respect to patents and project
proposals submitted.
Age-wise analysis of benefits: publications, project proposals, technological innovations & patents submitted……….contd.
System Wide/Institutional Impact
32
33
Impact of training at institution –
level – impact more in SAU
• Immediate application of training skills in
current work area
• High impact on presentation/writing skills
• High impact on networking / linkage
skills to enhance research
34
Impact of training at institution –
level -impact more in ICAR
• More number of trainees submittingjournal articles for publication
• Application of techniques learnt at trainingin developing new project proposals
• More joint publications with supervisors
35
Connections leading to Collaborations
Message:
• Developed connections
resulting in a collaborative
projects (55%)
Message
• Trainees initiated
communication resulting in a
collaborative project (47%)
• Organisations initiated
communication resulting in a
collaborative project (8%)
Professional recognition - Awards and promotions received post-training
Message:-
• Awards received
(27%)
• Institutional award
(17%)
• National award(7%)
• State-level award
(3%)
Message:-
• Promotions (35%)
Journal impact factor rating pre and post training (NAAS Rating)
Message:
Post training, the average capacity the scientists of publishing in high rated journals had increased. The figure indicates that
scientists had published papers in journal articles with rating 1-4.9 but post-training, they had been able to published more in
journal articles with rating 5-10.9.
0
0.2
0.4
0.6
0.8
1
1.2
11-11.9 12-12.9 14-14.9
Number of
papers published
pre-training
Number of paper
published post-
training
0
5
10
15
20
25
30
1-1.9 2-2.9 3-3.9 4-4.9 5-5.9 6-6.9 7-7.9 8-8.9 9-9.9 10-10.9 11-11.9 12-12.9 13-13.9 14-14.9
Percentage of papers published by the scientists in the respective journal impact factor category before training
Percentage of papers published by the scientists in the respective journal impact factor category after training
Benefit and Cost – Some Case Studies
38
Framework
7
Frontier Science Areas
11
Scientists
Marker Assisted
Selection
Fermentation
Tech
Nanotechnology
Genome RC
Carbon Trading
Nutraceuticals
Allele Mining
Science
Conventional Technology(Control)
New Technique Learnt
(Treatment)
Multiple Gains from New
Technology
Time
Convenience
Precision
Efficiency
Probability
Economy
Productivity
Profitability
Profitability
40
Theme
(number of scientist)
Conventional
Technology
New technology / Tool
Learnt
Product Application Average
B-C Ratio
Marker Assisted
Selection (123)
Phenotypic
Selection
Marker Assisted
Selection
HY Cattle Cattle
Improvement
11.35
PB - 1121 MAS (Disease
Resistant)
Disease
Resistant PB
Rice
Improvement
9.32
PB - 1121 MAS (Salt Tolerance) Salt Tolerant PB Rice
Improvement
9.31
Nanotechnology
(19)
Biochar Nano-patterning Nano-biochar Fertilizer
Economy
1.95
Photo
degradable
polymer
Bio-based polymer Biobased
polymeric films
Packaging 1.13
Conventional
nano-fibre
Nano-fibre (electro-
spinning technique)
Cellulose
nanofibre
Water/air filters 1.25
Fermentation
technology (15)
Conventional
Nisin
production
Improved Nisin
production
Nisin (biological
preservative)
Bio-
preservative
1.40
Bio-ethanol Improved Bio-ethanol Cellulosic
ethanol
Bio-ethanol 1.15
Benefit- Cost Ratio – Case Studies (1)
Figures in brackets indicate number of trainees.Note: Details worked out after discussion with the concerned/selected trained scientist/s. B-C ratios estimated with needed assumptions, being further checked and subjected to sensitivity analysis
41
Theme
(number of scientist)
Conventional
Technology
New technology /
Tool Learnt
Product Application Average
B-C Ratio
Carbon Trading /
Sequestration
(19)
IPCC Tire – I IPCC Tire – II and III Carbon Credits Carbon Trading 1.85
IPCC Tire – I IPCC Tire – II (GC –
for estimation of
GHGs)
GHG reduction
factors
GHGs
accounting /
inventory
2.52
Genome Resource
Conservation (13)
Genetic analysis
(w.o
automation)
Automation in
Genetic Analysis
(automation)
All economic
traits
Crop/ Animal
Improvement
3.88
Genome Resource
Conservation (Hort.)
Conventional
Breeding
DNA Marker Analysis Hybrid Crop
Improvement
1.009
Nutraceutical
(Fisheries)
(20)
Chemo-therapy
/ anti-biotics
Nutraceutical Nutraceuticals
Fish
Shrimp / Fish
Feed
1.17
Allele Mining
(14)
SSH cDNA library Microarray Identification of
special Genes
Shrimp / Fish
Feed
25 times
cost
efficient
Benefit- Cost Ratio - Case Studies (2)
Figures in brackets indicate number of trainees.Note: Details worked out after discussion with the concerned/selected trained scientist/s. B-C ratios estimated with needed assumptions, being further checked and subjected to sensitivity analysis
Thank you all
Dr. A. R. Rao, IASRI
Dr. Mukesh Kumar Rana, NBPGR
Dr. Manish Srivastava, IARI
Dr. (Ms.) Anju Arora, IARI
Dr. (Ms.) Sunita Singh, IARI
Dr. (Ms.) Sangeetha Lenka, IISS
Dr. M. S. Sekar, CIBA
Dr. Ambasankar, CIBA
Dr. Sachin Dey, NDRI
Dr. Sandip Gangil, CIAE
Dr. Vigneswaran, N., CIRCOT
Dr. A.K. Singh, IARI
Dr. Vij, NBAGR 42
National Trainings-Impact Assessment
43
44
National Training – Benefit Streams
18% change in journal articles accepted for publication and accepted as
a first author
30% change in journal articles accepted for publication in subject area
trained
OutputsAverage output
pre-trainingAverage output post-
training% change in
output
Journal articles accepted for publication 0.6 1.65 18
Journal articles accepted for publication as a first author 0.25 0.7 18
Journal articles accepted for publication in subject area trained 0.05 0.2 30
Annual reports/conference proceedings published as a first editor 0.3 0.35 2
45
Research/ Technical Skills
• Training objectives were met (100%)
• Training inspired new research ideas (85%)
• Training was complete and comprehensive(74%)
• More efficient at work (75%)
Presentation/Writing Skills
• Improved presentation/writing skills (65%)
Linkage & network skills
• Develop connections & linkages (55%)
Analysis of Skills - research, communication and linkage & network
Leadership Management Program – Reflections
Leadership Management Program – Outputs and Outcomes
Skills developed/improved
• Decision making skills• Management skills• Communication skills
• Useful in problem solving
• Better understanding of leadership process
• Developing a leadership plan for long-term perspective with effective utilization of institute resourcesFollow-up Actions
• Skills to be used for better research management process• Training modules developed for grassroots level workers and
stakeholders• Efficiency improved in managing programs• Collaborations developed
OUTPUTS
OUTCOMES
Response from Directors and Mentor/Facilitators
48
Response - Directors/Heads of the ICAR institutes & VCs of SAUs.
Research/Technical skills improved
• Analytical skills improved
• Improvement in formulating better project proposals
• Technical capacity improved (through new techniques learned)
Soft skills development
• Peer interaction improved
• Motivation improved• Communication skills
improved• Confidence to conduct
quality research• Special skills to do
demand driven research
Linkages developed
• International contacts developed
• Interactions with global knowledge resource
OUTCOMES
IMPACT
New Projects Initiated
Publishing reports
Help in current projects
Long-run projects planned to maintain
relations with global institutions
International Trainings
50
Director’s Evaluation of Impact of National Training
Broadened knowledge base and
forged linkages outside NARS system
Many externally projects are being
obtained
Establishing linkage with
private sector facilitated
Some examples of inter institutional
collaborations during CBP
51
Example 1
Example 2
• IARI • CSRI• ICAR• NRC on Seed Spices • CIAH • CSKHPKV • IIHR
MICHIGAN STATE UNIVERSITY
ICAR INSTITUTES
Conditions for Success and Way forward(based on our study findings and suggestions
from mentors/facilitators)
54
Selection criteria:
• Age- designation-education profile of trainee
“Young age- middle level- doctoral degree” combination more
potential for technology development
“Senior” level more suited for developing project proposals;
patents
• Gender balance
• Balancing ICAR and SAU scientists
• Pre training exposure to research
• Pre training publication
• Preference to proposals with innovative research ideas
• Preference to proposals that have better potential for
long-run collaborative research
Selection criteria, contd. ….
Selection criteria, contd. ….
• Preference to applicants who have identified a
faculty with similar research interests abroad
and initiated some contacts
• Preference to applicants who have their own
data/ samples to work on to ensure
accountability and ownership on output
57
Training design:
• Prioritize areas and themes for training
• Dovetail training duration to training purpose
Skill development – shortest duration
Updating expertise – medium duration (max. 12 weeks)
Frontier research – longest duration (min. 6 months)
• Orientation of trainees to acclimatize to foreign country conditions
Training design, contd. …..:
• Focus on quality and depth of training content
• More publications and project proposals during training
• Rewards for on-training publications
• Research project designed for long term collaborations between trainee and mentor (both at individual and institutional levels)
• Involvement with superiors in designing the training
Follow-ups/ monitoring:
• Post training follow-ups/ monitoring
Follow up on accomplishments using base line data
Faculty mentor travel back to monitor and assess progress
Mandatory output in terms of joint publications/continued research collaborations
Annual event for fostering networking among trainees on return to share experiences , assist is research and teaching
Post training multidisciplinary workshops.
Trained resource can be used for international / national
training in specific areas.
Creating central facility – investment intensive equipment –
Nanotech, MAS – to promote use of modern science
Attach trained resource to the industry for scaling up –
provide venture capital
Invest in periodic up-gradation of the skills of the trainees
61
Follow-ups/ monitoring , contd. ….
Implementation : • Flexible rules, regulations and policies
• Adequate physical space and facilities, infrastructure
including ICT
• Supportive leadership
• Encouragement from seniors and leaders
• Financial resources
Collaborative multidisciplinary research grants for long-runcollaborative research
Seed grants for short run collaborative research.
Financial supports to trainees during training like, bench fee, travelfunds etc.
62
Inventory :
• Generate discipline wise inventory
Resource persons (experts/mentors/facilitators/ trained scientists)
Training manuals
Suggestions and recommendations for future lines of work
• Inventory should be in the public domain – upload on ICAR website
63
Thank you
64