phd result jnu

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22 Sept 2023

24 sept 2023, about national testing agency.

The Ministry of Education (MoE), Government of India (GoI) has established the National Testing Agency (NTA) as an independent, autonomous, and self- sustained premier testing organization under the Societies Registration Act (1860) for conducting efficient, transparent, and international standardized tests in order to assess the competency of candidates for admission to premier higher education institutions with a mission to improve equity and quality in education by developing and administering research-based valid, reliable, efficient, transparent, fair and international level assessments.

NTA has created a system that is promoting teaching (by teachers), learning (by students), and assessment (by parents and institutions). NTA strongly believes in the quality, efficiency, effectiveness, equity, and security of assessments. To practice these values, NTA is constantly engaging with its stakeholders, viz. students, parents, teachers, experts, and partner institutions.

Ph.D Entrance Test - 2023

Ph.D Entrance Test is a national-level examination conducted by the National Testing Agency (NTA).

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JNUEE Result 2021: PhD result declared by JNU on jnuee.jnu.ac.in - How to download

JNUEE Result 2021 has been declared today, on November 18, 2021 for Ph.D course. Candidates who appeared for the exam, can check the result and download their marks now from the official website – jnuee.jnu.ac.in. Steps on how to download along with the direct link given here.

Key Highlights

• JNUEE Result 2021 has been declared today for Ph.D exam by Jawaharlal Nehru University, JNU.
• Candidates can check their result now by going to the official website - jnuee.jnu.ac.in or from the direct link given here.
• Those who secure merit in this result, will be appearing in the Viva Voce round.

Jawaharlal Nehru University Entrance Examination, JNUEE Result 2021 has been declared today – November 18, 2021 for students who appeared in the Ph.D exam. Jawaharlal Nehru University, JNU has activated the result link now. Candidates who appeared in this entrance exam, can check their result by going to the official website – jnuee.jnu.ac.in.  

JNUEE Result 2021 is for the exam that was held from September 20, 2021. Before this, the University had activated the 'marks update' link on its official website . Candidates were given a one-time opportunity to upload the marksheet of the qualifying degree. They were supposed to do so by logging into their accounts.  

Candidates must note that the result for other courses will be released in due course of time. Check below the step-by-step process on how to download Ph.D result.  

JNUEE Result 2021: How to check result and download marks 

• Candidates must visit the official website of Jawaharlal Nehru University Entrance Examination – jnuee.jnu.ac.in .  
• On the homepage, click on the link that reads, 'Ph.D entrance exam result 2021.' 
• Alternatively, candidates can click on the direct link given here to check JNUEE Result 2021 for Ph.D exam .  
• Enter your Application Number and Date of Birth and then click on login.  
• Your result will be displayed on your screen.  
• Download and print a copy of the same for future references.  

Also Read |  JNUEE Result 2021: JNU releases importance notice for results, to begin Viva Voce for PhD students soon – updates

Candidates must note that those who secure merit in JNUEE Result 2021 for Ph.D exam will have to appear in the viva voce round for the final admissions. The schedule for this will be released soon. JNU had mentioned previously that it was working closely with National Testing Agency, NTA for results declaration.  

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JNUEE PhD Result 2021 declared, direct link to check here

Jnuee phd result 2021 has been declared. candidates can check the result through the direct link given below. .

National Testing Agency, NTA has declared JNUEE PhD Result 2021 on November 18, 2021. Candidates who have appeared for Jawaharlal Nehru University Entrance Examination for Ph.D can check their results on the official site of JNU on jnuee.jnu.ac.in. 

Candidates who have qualified the examination will have to appear for the viva-voca round. The final merit list for PhD admission will be prepared with 70 per cent weightage to the CBT score and 30 per cent weightage to the viva round. To check the result candidates can follow these simple steps given below. 

Direct link to check result here 

JNUEE PhD Result 2021: How to check 

• Visit the official site of JNUEE on jnuee.jnu.ac.in.
• Click on JNUEE PhD Result 2021 link available on the home page.
• Enter the login details and click on submit.
• Your result will be displayed on the screen.
• Check the result and download the page.
• Keep a hard copy of the same for further need.

Meanwhile, JNU has extended the date for updating the qualifying degree/ marks. The date has been extended and window shall remain open from November 18, 19, 2021. The extension has been given to those candidates who were appearing/ whose results were not declared at the time of filing JNU entrance exam forms 2021-22. 

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JNUEE PhD Results Declared; Check Details Here

JNUEE PhD Result: The National Testing Agency (NTA) has declared the Jawaharlal Nehru University Entrance Examination (JNUEE - 2022) result today, January 10, 2023. The JNUEE 2022 exam for admission to Ph.D programmes offered by JNU was held by NTA from December 7 to 10, 2022. The exams were conducted computer-based test (CBT) mode in 39 cities across India at 43 centres. The JNUEE Ph.d exam 2022 was of objective type, comprising multiple choice questions.

Candidates who appeared in the exam will be able to view their JNUEE 2022 scorecard from the official website - jnuee.jnu.ac.in.

"Applicants of JNUEE can apply for maximum of three field of studies of their choice for the same level of programme. Accordingly 22,818 applications were received from 13,705 applicants for PhD programmes offered by JNU," the NTA in its notice said. 9,029 applicants appeared in the exam, as per the data shared by the NTA. Post exam, the NTA published the questions, provisional answer keys and the responses of the candidates between December 18-20, 2022.

The JNUEE PhD 2022 results were declared after reviewing the challenges raised by the candidates. JNU has also informed all the selected candidates in various courses to block their seats.

Steps to check JNUEE Ph.D Result 2022

Candidates are required to follow the steps given below JNUEE Ph.D Result

• Go to the official website of JNUEE at jnuee.jnu.ac.in.
• Click on the JNUEE Ph.D result download link.
• Enter the application number, date of birth, captcha.
• JNUEE result 2022 will appear on your screen.
• Check the scores and download for future use.

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JNUEE Result 2022 (OUT): Check JNU PhD Scorecard at jnuexams.nta.ac.in

Jnuee result 2022 (out): nta has released the result of jnuee 2022 for phd programmes. candidates can download the jnuee result 2022 at nta.ac.in or jnuexams.nta.ac.in. know details here.

JNUEE Result 2022 (OUT): As per the recent updates, the National Testing Agency (NTA) has announced the Jawaharlal Nehru University Entrance Examination (JNUEE) result 2022 today - January 10. Candidates can check their JNUEE PhD result 2022 at jnuexams.nta.ac.in. They will have to use their application number, date of birth and captcha code in the login window to check JNUEE PhD result 2022. 

The official notice states - “Applicants of JNUEE can apply for maximum of three field of studies of their choice for the same level of programme. Accordingly, 22,818 applications were received from 13,705 applicants for PhD programmes offered by JNU.” The JNUEE for admission to PhD programmes was held by the NTA from December 7 to 10, 2022.

How To Download JNUEE PhD Result 2022? 

• 1st Step - Go to the official website - jnuee.jnu.ac.in.
• 2nd Step - On the homepage, click on the JNUEE PhD result download link. 
• 3rd Step - A new page will appear on the screen.
• 4th Step - Enter application number, date of birth and captcha code. 
• 5th Step - The JNUEE Ph.D result will be displayed on the screen. 
• 6th Step - Download the same for future reference. 

Earlier, NTA released the provisional answer key of JNUEE PhD on December 18, 2022. Candidates were allowed to raise their objections in the provisional answer key till December 20, 2022. Based on those objections, NTA and JNU have released the result for PhD Admissions 2022. 

Also, candidates who have cleared the JNUEE PhD Entrance Exam have to appear for the Viva Voce round. Admissions are handled at the level of the University (JNU) for all PhD programmes offered by them. NTA will have no role in the selection process - transfer/cancellation/ conversion of seats etc.

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• Indian Universities /

JNU PhD 2023: Admissions (Via JNUEE and JRF), Eligibility, Fees, Dates

• Updated on  
• Jul 31, 2023

JNU PhD : Jawaharlal Nehru University (JNU) is one of India’s most prestigious academic institutions in India. Candidates aspiring to get enrolled on JNU’s PhD courses can apply either via the body’s proprietary exam, i.e., JNUEE ,  or via the JRF category. These are the two separate ways by which one can get admission for the said course at JNU. 

JNU Offers a wide assortment of lucrative PhD programmes that are designed to provide students with extensive knowledge in their respective domains. Students here can opt from 60 different lucrative PhD specialisations, namely PhD Life Science, PhD Economics, PhD English and so on. Read the article to know more about JNU PhD Admission, Important  Dates, Best Courses, and so on.

Table of Contents

• 1.1 JNU PhD Admission through JRF Category: Important Dates 2023
• 1.2 JNU PhD Admission through JNUEE Exam: Important Dates 2023
• 2.1 Eligibility Criteria for JNUEE (PhD) 
• 2.2 JNUEE PhD Exam Pattern 2023
• 2.3 JNUEE PhD Syllabus 2023
• 3.1 JNU PhD Application via JRF Category
• 3.2 How to Apply for JNU PhD Admission Under JRF? 
• 3.3 Eligibility and Selection Criteria for JRF Candidates 
• 4 JNU PhD Fees
• 5 List of JNU PhD Specialisations 
• 6.1 PhD Life Science 
• 6.2 PhD Economics 
• 6.3 PhD English 
• 6.4 PhD International Trade And Development
• 7 JNU Placement 2023

Also Read: Courses in JNU: UG, PG and Other Study Programmes

Important Dates for JNU PhD Admissions 2023

JNU has officially released admission dates for various programmes. Individuals interested in enrolling in any of the JNU courses must thus review the important dates to schedule their preparation work accordingly. 

JNU PhD Admission through JRF Category: Important Dates 2023

Candidates applying for PhD courses at JNU via JRF Category can refer to the following table to go through the crucial dates. 

JNU PhD Admission through JNUEE Exam: Important Dates 2023

Candidates intending to undertake the JNUEE exam to get admission into JNU’s PhD programmes can refer to the following table. 

Also Read: JNU Campus: Infrastructure, Facilities, and More

JNU PhD Admissions Via JNUEE

It is critical for aspirants who seek to pursue a doctoral degree (PhD) at JNU to qualify for the JNUEE entrance examination. JNUEE, a university-level entrance exam, is administered every year to admit meritorious candidates into JNU’s PhD, UG, PG, M.Phil and other integrated courses. JNUEE results for PhD Courses (2022) were declared on the 10th of January, 2023. 

Individuals aspiring to enrol for the PhD courses at JNU had to undertake the JNUEE (PhD) exam between 5th June and 12th June 2023. Candidates awaiting the final answer keys for JNUEE (PhD courses) exam can check them at the JNUEE PhD Results official website of the administrating body.  

Eligibility Criteria for JNUEE (PhD) 

Candidates who wish to pursue doctoral courses at the JNU must meet the following eligibility criteria: 

• Individuals must be holding a master’s degree in any similar subject with a minimum aggregate score of 50%. 
• Individuals must be holding citizenship in India. 
• Candidates hailing from international borders are also eligible for the said exam.
• Individuals below the age limit of 17 will not be considered eligible for the exam. 

Refer to the following table to understand the eligibility criteria for different specialisations for PhD. 

JNUEE PhD Exam Pattern 2023

Students who desire to pursue PhD degrees at JNU must take the JNUEE Exam (for PhD programmes). Students must become familiar with the exam pattern. When it comes to the JNUEE exam for PhD Courses, students sitting for the exam can anticipate being presented with multiple-choice questions from subjects studied at the graduate and postgraduate levels. Students must cover topics from subjects namely Mathematics, Statistics, and Computer Science when preparing. 

JNUEE PhD Syllabus 2023

Students must revise the prescribed syllabus for JNUEE to ace their tests. Those who wish to sit for the JNUEE Exam (for PhD courses) can refer to the following table to go through the syllabus. Have a look. 

JNU PhD Admissions Via JRF Category

Individuals who wish to pursue PhD courses from JNU can opt for the JRF (Junior Research Fellowship) category. Under this category, candidates can apply for admission without the need to sit for the JNUEE Exam. In other words, JRF candidates will be exempted from undertaking the JNUEE Entrance Exam. Those who wish to apply for admission under the said category may do so between the 5th of July and the 4th of August 2023. 

JNU PhD Application via JRF Category

Aspirants intending to apply for admission into JNU’s PhD programmes can register themselves between the 5th of July and the 4th of August 2023. Individuals must register on https://jnuee.jnu.ac.in to register for admission. 

How to Apply for JNU PhD Admission Under JRF? 

Those who wish to apply for JNU PhD admission under JRF can refer to the following steps. 

• Interested candidates must first visit JNU’s official admission portal to register themselves. 
• Aspirants must click on the ‘Apply for PhD programme’ option. 
• After doing so, one must click on ‘new registration’. 
• Candidates must log into their accounts by entering their designated credentials. 
• Once done with that, candidates must simply enter the requisite data, i.e., personal information and qualifications. 
• One must upload their photographs and signatures to ensure a successful registration process. 
• One must pay the requisite registration fee to complete the application process. 

Eligibility and Selection Criteria for JRF Candidates 

Candidates applying for JNU PhD admission via the JRF category must meet the following pre-requisites: 

• Candidates must have qualified for JRF CSIR/UGC National Eligibility Test (NET)/ICMR/AYUSH/DBT Examinations. 
• JRF Candidates are not required to undertake the JNUEE 2023 Exam for PhD admission. 
• Individuals are curated and selected based on their applications under the JRF category. Selected candidates are further called for their viva-voce rounds. Aspirants must clear the viva rounds to ensure a successful selection process. 
• One must acquire a score of 100% in their viva round to be selected.

JNU PhD Fees

The average tuition fees for pursuing PhD courses in JNU range between INR 395 to INR 1,391. Refer to the following table to go through the JNU PhD Fees for different specialisations. 

List of JNU PhD Specialisations 

Students can choose from 60 different PhD specialisations at JNU. The complete list of specialisations is given below.

Top JNU PhD Courses 

Each of these courses has been meticulously planned and structured with the aim of providing students with the best possible quality of education. Some major PhD courses available at the JNU are PhD Life Science, PhD Economics, PhD English, PhD Law & Governance, and PhD Ancient History. Let’s Have a look. 

PhD Life Science 

This 3-year full-time JNU PhD programme focuses on honing one’s knowledge in the study of living organisms. The course aims to provide students with extensive knowledge of Biology, Ecology, Evolution and Neuroscience. Those who wish to opt for the course must be having a prior understanding of the stated subjects as it is an advanced level course. 

PhD Economics 

PhD Economics is one of the most sought-after doctoral courses at the JNU. The total cost of this three-year programme is around INR 3,949 (r years). The course is meant for those who wish to learn more about macroeconomics and microeconomics. Individuals who aspire to carve a teaching career in Economics or wish to continue their research work in the domains of Economics must definitely opt for this doctoral programme at JNU. 

PhD English 

Individuals who wish to gain an in-depth knowledge of the English language can opt for this three-year doctoral programme. The total tuition fee for the programme is INR 3,949. The programme is meant for those who wish to hone and enhance their reading, learning and writing skills in English. The curriculum for the course is designed to provide students with an extensive knowledge of   different theories, texts, dialects and sects of the English language.

PhD International Trade And Development

This three-year on-campus doctoral programme at JNU aims at shaping young minds into capable professionals who are able to prove their mettle in the private, nonprofit, and government sectors. Individuals who wish to carve their careers in the domain of international business are encouraged to opt for the said course. The total cost for the said programme is INR 3,959 (for three years). 

JNU Placement 2023

As of 2023, JNU UG students managed to bag a median salary package of INR 6 LPA, while PG graduates were placed with an average package of INR 7.95 LPA. This year, corporations such as McKinsey, Legato, Adobe, Google, Samsung, Sapient, Siemens, Infosys, and HCL, participated in the recruitment drive. 

The academic year of 2021-2022 was a successful run for JNU as it managed to conduct a lucrative recruitment drive. JNU’s Placement cell worked diligently day in and day out to bring in some of the biggest names in the industry. Students in that year were placed with higher salary packages in comparison to other years. The average salary stood at a whopping INR 8 LPA during 2021-22. Some of the key players who participated in the recruitment drive were mega corporations including  SIEMENS, Ramco, Sapient, Samsung, Quark, Oracle, Optum, McKinsey & Company, Legato, Adobe, Amazon, Genpact and many more.

CLICK HERE to know everything about JNU PhD

Individuals interested in enrolling in JNU’s PhD programmes must take the JNUEE entrance exam. In terms of difficulty students pursuing a PhD in JNU get paid? Yes, students pursuing a PhD at JNU get paid around INR 1.2 lakhs to 5.5 lakhs on a yearly basis.  Candidates who wish to pursue PhD courses from JNU are required to qualify for the JNUEE Entrance Exam. JNU is notable for featuring 60 lucrative PhD programmes. The said institution offers such courses via sixteen schools/centres.lty, the exam is regarded as one of the most rigorous in the country, making it more difficult for students to qualify. As a result, it is vital to devote sufficient time to exam preparation.

No, JRF is not compulsory for JNU PhD admission. Individuals who wish to pursue PhD courses from JNU are required to sit for the JNUEE (CBT) Exam. 

There are 60 specialisations available for PhD courses at JNU. 

Individuals who wish to get admitted into JNU’s PhD courses must apply for their preferred disciplines online at their official website for admissions. 

Individuals who wish to pursue a PhD course from JNU must go through the prescribed eligibility criteria, select their preferred domain of research,  apply for their course (online), pay the requisite registration fee, sit for the interview round,  undertake the JNUEE exam and acquire the eligible scores.

For more information, you may check our Indian Universities page. Stay tuned to Leverage Edu for information on higher education.   

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NTA Ph.D Entrance Result 2024, Check Dates, Merit List @phd-entrance.samarth.ac.in

Uddipana Choudhury

Content Writer | Updated On - Aug 2, 2024

NTA Ph.D results will be announced tentatively in November 2024 . You can check the NTA Ph.D result 2024 on the official website- phd-entrance.samarth.ac.in.  The score and the candidate’s data will be shared to the University where he/she applied for. Each University will draw the merit list based on the   score provided. 

NTA Ph.D Entrance Exam is conducted for Ph.D admission in Universities including DU, JNU, BHU and BBAU. For more related details you can check the official website of NTA.

Those who have appeared for the NTA Ph.D Entrance Exam   2024 can check the results by following the steps given below. 

NTA Ph.D Entrance Exam Result 2024 Dates

Candidates can check the expected dates for NTA Ph.D Entrance Exam from the below table:

NTA Ph.D Entrance Exam Result 2024 Highlights

How to Check NTA Ph.D Entrance Exam Result 2024?

Candidates who want to check the result online have to follow the below mentioned procedure to check NTA Ph.D Entrance Exam Result-

• Visit the official website - phd-entrance.samarth.ac.in
• Click on the link showing - ‘NTA Ph.D Entrance Exam Result’.
• On the login page, enter your login details and click on submit.
• Therefore, check your score and rank. Make a print out of the result for further reference.

Note: If NTA releases Ph.D Entrance Exam Result in the form of a merit list then candidates have to download the PDF from the official website and find their roll number and rank.

NTA Ph.D Entrance Exam Result 2024 - NTA Score

The admission using the NTA Score is done by following the below way:

• NTA Score of Ph.D Entrance Exam 2024 for DU, JNU, BHU and BBAU would be valid for admission to the academic year 2024-25 only.
• Score and candidate data would be shared with the university where he/she has applied.
• Based on the score provided by NTA, each University will draw the merit list.
• Evaluation of MCQs of all test papers will be carried out using final answer keys and the actual marks obtained by a candidate will be considered further for computation of the result of Ph.D Entrance Test for DU, JNU, BHU and BBAU 2024.

NTA Ph.D Entrance Exam Result 2024: Rechecking and Revaluation

• The result for NTA Ph.D Entrance Test 2024 will be prepared based on the final answer keys. No grievance will be entertained with regard to Answer Keys after declaration of the result.
• The Marks obtained by a candidate will be considered for further computation of the result of Ph.D Entrance Exam 2024.
• There will be no rechecking/revaluation of the result. No correspondence in this regard will be entertained.
• Candidates can download NTA Ph.D Entrance Exam Scorecard from the official website - phd-entrance.samarth.ac.in.
• No individual scorecard will be dispatched to the candidates.

Frequently Asked Questions

Ques. What is the passing mark for NTA Ph.D Entrance Exam 2024?

Ans. Participated candidates will have to secure 50-55% marks to qualify the exam. Admission to the PG programs will be granted based on the interview.

Ques. How difficult is the NTA Ph.D Entrance Exam?

Ans. They range from very very hard, to about average (average being no harder than the final of an upper level class in your field), and mostly depends on how selective your school/department wishes to be.

Ques. How can NTA Ph.D Entrance Exam Result be downloaded?

Ans. NTA Ph.D Entrance Exam can be downloaded from the official website - phd-entrance.samarth.ac.in by using the login credentials.

Ques. When will NTA Ph.D Entrance Exam Result 2024 be released?

Ans. NTA Ph.D Entrance Exam result is expected to be released in November 2024. The result can be released in the form of a merit list and will be shared to the applied university.

Ques. How can I check my NTA Ph.D. results 2024?

Ans. To check your NTA Ph.D results 2024, you need to visit the official website phd-entrance.samarth.ac.in. Then, click on ‘NTA Ph.D Entrance Exam Result’. A login page will appear, enter you login credentials. The NTA Ph.D result 2024 will be displayed on the screen.

* The article might have information for the previous academic years, which will be updated soon subject to the notification issued by the University/College.

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• NATURE INDEX
• 29 August 2024

Japan moves to halt long-term postgraduate decline by tripling number of PhD graduates

• Tim Hornyak 0

Tim Hornyak is a freelance science and technology journalist in Tokyo.

You can also search for this author in PubMed   Google Scholar

A PhD student works in a clean room at the University of Tokyo. Credit: Yuichi Yamazaki/AFP via Getty

In response to a decline in the number of PhD holders in Japan, the Japanese government has announced plans to not only stop the trend but reverse it, by tripling the number by 2040.

Japan is the only major economy that has recorded a dip in PhD numbers since 2000. In 2022, there were 14,382 new PhD admissions across the country — down 21% from a high of 18,232 in 2003.

As a proportion of the population, there are now fewer PhD holders in Japan than in many other leading research countries. According to Japan’s National Institute of Science and Technology Policy (NISTEP), in 2020, the country had 123 PhD graduates per million people, well below the rate of 315 per million in Germany and 313 per million in the United Kingdom for that year, and 285 per million in the United States in 2019.

A survey published by NISTEP in 2021 revealed that many doctoral students in Japan feel demoralized because of financial uncertainty, career insecurity and a lack of career progression.

To address the problem, Japan’s Ministry of Education, Culture, Sports, Science and Technology (MEXT) announced a three-pillared plan in March, with a focus on boosting career opportunities as well as institutional support and outreach for PhD students. The government is hoping to promote a cultural shift that raises the status of PhD holders in Japanese society.

“We want to create an environment that increases the number of people aiming for doctoral degrees, produces many excellent candidates, and realizes a fruitful life for each candidate and the sustainable development of society as a whole,” Mitsunari Yoshida, director of the Policy Division in MEXT’s Higher Education Bureau, told Nature Index.

Career choices

The first pillar of the initiative focuses on diversifying career choices, to ensure that doctoral candidates have a more active role in research outside academia, such as in local and central government, start-up companies and other private-sector groups.

2024 Research Leaders

This focus on industry and government roles aims to address a long-standing cultural issue in Japan, namely that having a PhD might actually limit someone’s chances of being hired.

“The greatest obstacle is the perception that once one gets a PhD in a subject, one is regarded as an expert in that particular field,” says Ken Mogi, a researcher in neuroscience at Sony Computer Science Laboratories in Tokyo, and a visiting academic at the University of Tokyo. “With that image comes the assumption that a person with a PhD is inflexible in work in the real world. For that reason, Japanese companies are typically not forthcoming in employing people with PhDs, discouraging students to consider a career with a PhD.”

MEXT plans to promote long-term, paid internships for PhD students in the private sector, as part of a broader effort to entrench internships in Japanese society.

Symbolic of this is Cooperative Education Through Research Internships, a programme introduced in 2021 with the support of 45 universities and 45 companies, including major Japanese brands. The paid internships run for at least two months, are eligible for academic credit, and aim to support doctoral researchers by matching them to companies and diversifying their career options. The ministry wants to increase the number of PhD candidates in these internships to 5,000 by 2030, up from 3,000 as of May this year.

Boosting support

As its second pillar, MEXT wants to raise the quality of graduate schools by providing extra funding and tracking their progress.

MEXT will part-fund PhD students’ living and research expenses through the Support for Pioneering Research Initiated by the Next Generation (SPRING) scheme, which is run by the Japan Science and Technology Agency to support outstanding doctoral students; and the Japan Society for the Promotion of Science’s Research Fellowship for Young Scientists programme, which supports doctoral students to pursue innovative research of their own choosing.

“Financial issues are significant in Japan, and many PhD students are struggling," says Tomokazu Iwabuchi, a PhD student in urban planning at Kyushu University in Fukuoka.

After years of taking on part-time jobs during his master’s programme, Iwabuchi says he can now spend more time focusing on PhD research because he was chosen for the university’s Future-Creation course, which is part of the SPRING programme. Doctoral students on the programme receive ¥200,000 (US$1,360) per month to cover living expenses and language training, up to ¥850,000 yen per year in research expenses, and a 50% reduction in tuition fees.

In 2023, Iwabuchi started his own consulting business rooted in his research on urban planning and geographic information system (GIS) data. “I’m really happy to hear that the government is putting more resources into supporting PhD students,” he says. “I hope they will have more career options in the near future.”

Strengthening motivation

The third pillar is about boosting student motivation by supporting more outreach programmes. One example is the Future Doctoral Festival, an annual gathering in Tokyo at which doctoral students give presentations and take part in panel discussions related to their research. The goal of initiatives such as this is to showcase the appeal of pursuing a PhD, not just to students, but also to leading figures in the public and private sectors.

Ranny Herdiantoputri, a doctoral student in oral pathology at the Tokyo Medical and Dental University welcomes this outreach, but says more attention must be given to the mental health of prospective PhD students, especially those from overseas who might struggle with the Japanese language and feelings of isolation.

“Students can suffer from imposter syndrome and anxiety, and wonder, ‘Am I really good enough for this?’,” says Herdiantoputri. “Without proper support, outreach gatherings can make it worse.” She adds that teaching jobs at Japan’s public universities are almost impossible to get, and she plans to return to her home country, Indonesia, after her degree.

Will it work?

Koichi Sumikura, who studies science and technology policy at the National Graduate Institute for Policy Studies in Tokyo, thinks that a change in mindset among those in industry is a must. “A majority of industry managers in Japan consider that the expertise and the area of interest of PhD holders are too narrow and do not fit their business,” he says. “However, PhD holders tend to be trained for acquiring a wider field of view.”

Sumikura emphasizes the importance of PhD programmes teaching skills that are relevant to industry. “PhD holders themselves should be trained not only in a specific academic expertise, but also general scientific knowledge, communication skills and business and social literacy,” says Sumikura.

Nobuko Kobayashi, who works for EY-Parthenon, a consultancy based in Boston, Massachusetts, and who writes about innovation and human resources in the Japanese media, says she hopes that Japan will consider and support entrepreneurship opportunities for its PhD holders.

“It’s important that universities strengthen education and opportunities around entrepreneurship, so students can bridge their research with real-world applications,” says Kobayashi. One encouraging factor is the increase in start-ups in Japan. In particular, she says, the number of start-ups spun off from Japanese universities has increased every year, and these firms “also hire significantly more PhD graduates compared to other Japanese companies”.

It is to soon to tell whether the measures Japan is now undertaking can motivate its doctoral students, change hiring practices and overhaul its research culture. But Sumikura agrees that the effort is worthwhile. “It is not easy to achieve that goal, but it is worth trying,” Sumikura says.

doi: https://doi.org/10.1038/d41586-024-02718-6

Nature Index’s news and supplement content is editorially independent of its publisher, Springer Nature. For more information about Nature Index, see the homepage .

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Our Faculty and PhD Student Win Best Paper at SIGCOMM 2024

PhD student Yuang Shi and Assoc Prof Wei Tsang Ooi have been recognized with the best paper award at the ACM Special Interest Group on Data Communication workshop on Emerging Multimedia Systems 2024 . Their paper, "Multi-frame Bitrate Allocation of Dynamic 3D Gaussian Splatting Streaming Over Dynamic Networks”, offers innovative solutions for streaming 3D content over varying network conditions.

They collaborated with Taiwan’s National Tsing Hua University and National Yang Ming Chiao Tung University to create algorithms that efficiently allocate bitrate across multiple 3DGS frames.

This research improves adaptive streaming of complex 3D content, with potential uses in VR, remote visualization, and interactive 3D experiences.

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Stock market today: US stocks slip as traders count down to Nvidia earnings

• US stocks traded mostly flat as investors looked toward Nvidia's earnings report due after the close.
• Markets are eyeing another earnings beat, but there's also caution around chip delays.
• Traders are also eyeing comments from the Atlanta Fed President for more clues on rate cuts.

US stocks inched lower on Wednesday as traders awaited the upcoming Nvidia earnings report . All three benchmark indexes dipped slightly in the red, while Nvidia shares traded 1% higher.

Expectations are high for the chipmaker, with investors looking for another earnings beat and solid clues about how the massive investment in AI is working out for Nvidia's customers.

The firm's results have the potential to fuel a major swing in the market, with Goldman Sachs noting on Tuesday that the report could spark a $300 billion swing for Nvidia's stock based on options pricing this week.

The stock is already trading close to record highs, adding to the risk that a small miss on expectations could spur a big move down.

"For equities, all attention is now on Nvidia's earnings release tonight, which has helped to drive significant moves recent quarters," Deutsche Bank strategists said in a note Wednesday morning. "Bear in mind that Nvidia's share price is already up +159% on a YTD basis, making it the top performer in the entire S&P 500, and it has risen by more than +1000% since its low in October 2022."

Traders are also waiting on comments from Atlanta Fed President Raphael Bostic, who's scheduled to speak after the closing bell. His remarks could provide more guidance on the path of Fed rate cuts this year, with investors pricing in as many as 150 basis points worth of cuts by year-end, according to the CME FedWatch tool .

Here's where US indexes stood shortly after the opening bell on Monday:

• S&P 500 : 5,623.67, down 0.04%
• Dow Jones Industrial Average : 41,252.06, down 0.01% (-1.56 points)
• Nasdaq composite : 17,748.91, down 0.07%

Here's what else is going on today:

• Nvidia's earnings report could spark a $300 billion swing in the stock , Goldman Sachs said.
• The number of bitcoin millionaires has soared 111% over the last year .

In commodities, bonds, and crypto:

• West Texas Intermediate crude oil slipped 1.02% to $74.75 a barrel. Brent crude , the international benchmark, dipped 0.92% to $77.93 a barrel.
• Gold moved lower 0.9% to $2,502.25 an ounce.
• The 10-year Treasury yield was flat at 3.825%.
• Bitcoin dropped 4% to $59,827.

• Main content

• Study Protocol
• Open access
• Published: 26 August 2024

Learning effect of online versus onsite education in health and medical scholarship – protocol for a cluster randomized trial

• Rie Raffing 1 ,
• Lars Konge 2 &
• Hanne Tønnesen 1  

BMC Medical Education volume  24 , Article number:  927 ( 2024 ) Cite this article

123 Accesses

Metrics details

The disruption of health and medical education by the COVID-19 pandemic made educators question the effect of online setting on students’ learning, motivation, self-efficacy and preference. In light of the health care staff shortage online scalable education seemed relevant. Reviews on the effect of online medical education called for high quality RCTs, which are increasingly relevant with rapid technological development and widespread adaption of online learning in universities. The objective of this trial is to compare standardized and feasible outcomes of an online and an onsite setting of a research course regarding the efficacy for PhD students within health and medical sciences: Primarily on learning of research methodology and secondly on preference, motivation, self-efficacy on short term and academic achievements on long term. Based on the authors experience with conducting courses during the pandemic, the hypothesis is that student preferred onsite setting is different to online setting.

Cluster randomized trial with two parallel groups. Two PhD research training courses at the University of Copenhagen are randomized to online (Zoom) or onsite (The Parker Institute, Denmark) setting. Enrolled students are invited to participate in the study. Primary outcome is short term learning. Secondary outcomes are short term preference, motivation, self-efficacy, and long-term academic achievements. Standardized, reproducible and feasible outcomes will be measured by tailor made multiple choice questionnaires, evaluation survey, frequently used Intrinsic Motivation Inventory, Single Item Self-Efficacy Question, and Google Scholar publication data. Sample size is calculated to 20 clusters and courses are randomized by a computer random number generator. Statistical analyses will be performed blinded by an external statistical expert.

Primary outcome and secondary significant outcomes will be compared and contrasted with relevant literature. Limitations include geographical setting; bias include lack of blinding and strengths are robust assessment methods in a well-established conceptual framework. Generalizability to PhD education in other disciplines is high. Results of this study will both have implications for students and educators involved in research training courses in health and medical education and for the patients who ultimately benefits from this training.

Trial registration

Retrospectively registered at ClinicalTrials.gov: NCT05736627. SPIRIT guidelines are followed.

Peer Review reports

Medical education was utterly disrupted for two years by the COVID-19 pandemic. In the midst of rearranging courses and adapting to online platforms we, with lecturers and course managers around the globe, wondered what the conversion to online setting did to students’ learning, motivation and self-efficacy [ 1 , 2 , 3 ]. What the long-term consequences would be [ 4 ] and if scalable online medical education should play a greater role in the future [ 5 ] seemed relevant and appealing questions in a time when health care professionals are in demand. Our experience of performing research training during the pandemic was that although PhD students were grateful for courses being available, they found it difficult to concentrate related to the long screen hours. We sensed that most students preferred an onsite setting and perceived online courses a temporary and inferior necessity. The question is if this impacted their learning?

Since the common use of the internet in medical education, systematic reviews have sought to answer if there is a difference in learning effect when taught online compared to onsite. Although authors conclude that online learning may be equivalent to onsite in effect, they agree that studies are heterogeneous and small [ 6 , 7 ], with low quality of the evidence [ 8 , 9 ]. They therefore call for more robust and adequately powered high-quality RCTs to confirm their findings and suggest that students’ preferences in online learning should be investigated [ 7 , 8 , 9 ].

This uncovers two knowledge gaps: I) High-quality RCTs on online versus onsite learning in health and medical education and II) Studies on students’ preferences in online learning.

Recently solid RCTs have been performed on the topic of web-based theoretical learning of research methods among health professionals [ 10 , 11 ]. However, these studies are on asynchronous courses among medical or master students with short term outcomes.

This uncovers three additional knowledge gaps: III) Studies on synchronous online learning IV) among PhD students of health and medical education V) with long term measurement of outcomes.

The rapid technological development including artificial intelligence (AI) and widespread adaption as well as application of online learning forced by the pandemic, has made online learning well-established. It represents high resolution live synchronic settings which is available on a variety of platforms with integrated AI and options for interaction with and among students, chat and break out rooms, and exterior digital tools for teachers [ 12 , 13 , 14 ]. Thus, investigating online learning today may be quite different than before the pandemic. On one hand, it could seem plausible that this technological development would make a difference in favour of online learning which could not be found in previous reviews of the evidence. On the other hand, the personal face-to-face interaction during onsite learning may still be more beneficial for the learning process and combined with our experience of students finding it difficult to concentrate when online during the pandemic we hypothesize that outcomes of the onsite setting are different from the online setting.

To support a robust study, we design it as a cluster randomized trial. Moreover, we use the well-established and widely used Kirkpatrick’s conceptual framework for evaluating learning as a lens to assess our outcomes [ 15 ]. Thus, to fill the above-mentioned knowledge gaps, the objective of this trial is to compare a synchronous online and an in-person onsite setting of a research course regarding the efficacy for PhD students within the health and medical sciences:

Primarily on theoretical learning of research methodology and

Secondly on

◦ Preference, motivation, self-efficacy on short term

◦ Academic achievements on long term

Trial design

This study protocol covers synchronous online and in-person onsite setting of research courses testing the efficacy for PhD students. It is a two parallel arms cluster randomized trial (Fig.  1 ).

Consort flow diagram

The study measures baseline and post intervention. Baseline variables and knowledge scores are obtained at the first day of the course, post intervention measurement is obtained the last day of the course (short term) and monthly for 24 months (long term).

Randomization is stratified giving 1:1 allocation ratio of the courses. As the number of participants within each course might differ, the allocation ratio of participants in the study will not fully be equal and 1:1 balanced.

Study setting

The study site is The Parker Institute at Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Denmark. From here the courses are organized and run online and onsite. The course programs and time schedules, the learning objective, the course management, the lecturers, and the delivery are identical in the two settings. The teachers use the same introductory presentations followed by training in break out groups, feed-back and discussions. For the online group, the setting is organized as meetings in the online collaboration tool Zoom® [ 16 ] using the basic available technicalities such as screen sharing, chat function for comments, and breakout rooms and other basics digital tools if preferred. The online version of the course is synchronous with live education and interaction. For the onsite group, the setting is the physical classroom at the learning facilities at the Parker Institute. Coffee and tea as well as simple sandwiches and bottles of water, which facilitate sociality, are available at the onsite setting. The participants in the online setting must get their food and drink by themselves, but online sociality is made possible by not closing down the online room during the breaks. The research methodology courses included in the study are “Practical Course in Systematic Review Technique in Clinical Research”, (see course programme in appendix 1) and “Getting started: Writing your first manuscript for publication” [ 17 ] (see course programme in appendix 2). The two courses both have 12 seats and last either three or three and a half days resulting in 2.2 and 2.6 ECTS credits, respectively. They are offered by the PhD School of the Faculty of Health and Medical Sciences, University of Copenhagen. Both courses are available and covered by the annual tuition fee for all PhD students enrolled at a Danish university.

Eligibility criteria

Inclusion criteria for participants: All PhD students enrolled on the PhD courses participate after informed consent: “Practical Course in Systematic Review Technique in Clinical Research” and “Getting started: Writing your first manuscript for publication” at the PhD School of the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.

Exclusion criteria for participants: Declining to participate and withdrawal of informed consent.

Informed consent

The PhD students at the PhD School at the Faculty of Health Sciences, University of Copenhagen participate after informed consent, taken by the daily project leader, allowing evaluation data from the course to be used after pseudo-anonymization in the project. They are informed in a welcome letter approximately three weeks prior to the course and again in the introduction the first course day. They register their consent on the first course day (Appendix 3). Declining to participate in the project does not influence their participation in the course.

Interventions

Online course settings will be compared to onsite course settings. We test if the onsite setting is different to online. Online learning is increasing but onsite learning is still the preferred educational setting in a medical context. In this case onsite learning represents “usual care”. The online course setting is meetings in Zoom using the technicalities available such as chat and breakout rooms. The onsite setting is the learning facilities, at the Parker Institute, Bispebjerg and Frederiksberg Hospital, The Capital Region, University of Copenhagen, Denmark.

The course settings are not expected to harm the participants, but should a request be made to discontinue the course or change setting this will be met, and the participant taken out of the study. Course participants are allowed to take part in relevant concomitant courses or other interventions during the trial.

Strategies to improve adherence to interventions

Course participants are motivated to complete the course irrespectively of the setting because it bears ECTS-points for their PhD education and adds to the mandatory number of ECTS-points. Thus, we expect adherence to be the same in both groups. However, we monitor their presence in the course and allocate time during class for testing the short-term outcomes ( motivation, self-efficacy, preference and learning). We encourage and, if necessary, repeatedly remind them to register with Google Scholar for our testing of the long-term outcome (academic achievement).

Outcomes are related to the Kirkpatrick model for evaluating learning (Fig.  2 ) which divides outcomes into four different levels; Reaction which includes for example motivation, self-efficacy and preferences, Learning which includes knowledge acquisition, Behaviour for practical application of skills when back at the job (not included in our outcomes), and Results for impact for end-users which includes for example academic achievements in the form of scientific articles [ 18 , 19 , 20 ].

The Kirkpatrick model

Primary outcome

The primary outcome is short term learning (Kirkpatrick level 2).

Learning is assessed by a Multiple-Choice Questionnaire (MCQ) developed prior to the RCT specifically for this setting (Appendix 4). First the lecturers of the two courses were contacted and asked to provide five multiple choice questions presented as a stem with three answer options; one correct answer and two distractors. The questions should be related to core elements of their teaching under the heading of research training. The questions were set up to test the cognition of the students at the levels of "Knows" or "Knows how" according to Miller's Pyramid of Competence and not their behaviour [ 21 ]. Six of the course lecturers responded and out of this material all the questions which covered curriculum of both courses were selected. It was tested on 10 PhD students and within the lecturer group, revised after an item analysis and English language revised. The MCQ ended up containing 25 questions. The MCQ is filled in at baseline and repeated at the end of the course. The primary outcomes based on the MCQ is estimated as the score of learning calculated as number of correct answers out of 25 after the course. A decrease of points of the MCQ in the intervention groups denotes a deterioration of learning. In the MCQ the minimum score is 0 and 25 is maximum, where 19 indicates passing the course.

Furthermore, as secondary outcome, this outcome measurement will be categorized as binary outcome to determine passed/failed of the course defined by 75% (19/25) correct answers.

The learning score will be computed on group and individual level and compared regarding continued outcomes by the Mann–Whitney test comparing the learning score of the online and onsite groups. Regarding the binomial outcome of learning (passed/failed) data will be analysed by the Fisher’s exact test on an intention-to-treat basis between the online and onsite. The results will be presented as median and range and as mean and standard deviations, for possible future use in meta-analyses.

Secondary outcomes

Motivation assessment post course: Motivation level is measured by the Intrinsic Motivation Inventory (IMI) Scale [ 22 ] (Appendix 5). The IMI items were randomized by random.org on the 4th of August 2022. It contains 12 items to be assessed by the students on a 7-point Likert scale where 1 is “Not at all true”, 4 is “Somewhat true” and 7 is “Very true”. The motivation score will be computed on group and individual level and will then be tested by the Mann–Whitney of the online and onsite group.

Self-efficacy assessment post course: Self-efficacy level is measured by a single-item measure developed and validated by Williams and Smith [ 23 ] (Appendix 6). It is assessed by the students on a scale from 1–10 where 1 is “Strongly disagree” and 10 is “Strongly agree”. The self-efficacy score will be computed on group and individual level and tested by a Mann–Whitney test to compare the self-efficacy score of the online and onsite group.

Preference assessment post course: Preference is measured as part of the general course satisfaction evaluation with the question “If you had the option to choose, which form would you prefer this course to have?” with the options “onsite form” and “online form”.

Academic achievement assessment is based on 24 monthly measurements post course of number of publications, number of citations, h-index, i10-index. This data is collected through the Google Scholar Profiles [ 24 ] of the students as this database covers most scientific journals. Associations between onsite/online and long-term academic will be examined with Kaplan Meyer and log rank test with a significance level of 0.05.

Participant timeline

Enrolment for the course at the Faculty of Health Sciences, University of Copenhagen, Denmark, becomes available when it is published in the course catalogue. In the course description the course location is “To be announced”. Approximately 3–4 weeks before the course begins, the participant list is finalized, and students receive a welcome letter containing course details, including their allocation to either the online or onsite setting. On the first day of the course, oral information is provided, and participants provide informed consent, baseline variables, and base line knowledge scores.

The last day of scheduled activities the following scores are collected, knowledge, motivation, self-efficacy, setting preference, and academic achievement. To track students' long term academic achievements, follow-ups are conducted monthly for a period of 24 months, with assessments occurring within one week of the last course day (Table  1 ).

Sample size

The power calculation is based on the main outcome, theoretical learning on short term. For the sample size determination, we considered 12 available seats for participants in each course. To achieve statistical power, we aimed for 8 clusters in both online and onsite arms (in total 16 clusters) to detect an increase in learning outcome of 20% (learning outcome increase of 5 points). We considered an intraclass correlation coefficient of 0.02, a standard deviation of 10, a power of 80%, and a two-sided alpha level of 5%. The Allocation Ratio was set at 1, implying an equal number of subjects in both online and onsite group.

Considering a dropout up to 2 students per course, equivalent to 17%, we determined that a total of 112 participants would be needed. This calculation factored in 10 clusters of 12 participants per study arm, which we deemed sufficient to assess any changes in learning outcome.

The sample size was estimated using the function n4means from the R package CRTSize [ 25 ].

Recruitment

Participants are PhD students enrolled in 10 courses of “Practical Course in Systematic Review Technique in Clinical Research” and 10 courses of “Getting started: Writing your first manuscript for publication” at the PhD School of the Faculty of Health Sciences, University of Copenhagen, Denmark.

Assignment of interventions: allocation

Randomization will be performed on course-level. The courses are randomized by a computer random number generator [ 26 ]. To get a balanced randomization per year, 2 sets with 2 unique random integers in each, taken from the 1–4 range is requested.

The setting is not included in the course catalogue of the PhD School and thus allocation to online or onsite is concealed until 3–4 weeks before course commencement when a welcome letter with course information including allocation to online or onsite setting is distributed to the students. The lecturers are also informed of the course setting at this time point. If students withdraw from the course after being informed of the setting, a letter is sent to them enquiring of the reason for withdrawal and reason is recorded (Appendix 7).

The allocation sequence is generated by a computer random number generator (random.org). The participants and the lecturers sign up for the course without knowing the course setting (online or onsite) until 3–4 weeks before the course.

Assignment of interventions: blinding

Due to the nature of the study, it is not possible to blind trial participants or lecturers. The outcomes are reported by the participants directly in an online form, thus being blinded for the outcome assessor, but not for the individual participant. The data collection for the long-term follow-up regarding academic achievements is conducted without blinding. However, the external researcher analysing the data will be blinded.

Data collection and management

Data will be collected by the project leader (Table  1 ). Baseline variables and post course knowledge, motivation, and self-efficacy are self-reported through questionnaires in SurveyXact® [ 27 ]. Academic achievements are collected through Google Scholar profiles of the participants.

Given that we are using participant assessments and evaluations for research purposes, all data collection – except for monthly follow-up of academic achievements after the course – takes place either in the immediate beginning or ending of the course and therefore we expect participant retention to be high.

Data will be downloaded from SurveyXact and stored in a locked and logged drive on a computer belonging to the Capital Region of Denmark. Only the project leader has access to the data.

This project conduct is following the Danish Data Protection Agency guidelines of the European GDPR throughout the trial. Following the end of the trial, data will be stored at the Danish National Data Archive which fulfil Danish and European guidelines for data protection and management.

Statistical methods

Data is anonymized and blinded before the analyses. Analyses are performed by a researcher not otherwise involved in the inclusion or randomization, data collection or handling. All statistical tests will be testing the null hypotheses assuming the two arms of the trial being equal based on corresponding estimates. Analysis of primary outcome on short-term learning will be started once all data has been collected for all individuals in the last included course. Analyses of long-term academic achievement will be started at end of follow-up.

Baseline characteristics including both course- and individual level information will be presented. Table 2 presents the available data on baseline.

We will use multivariate analysis for identification of the most important predictors (motivation, self-efficacy, sex, educational background, and knowledge) for best effect on short and long term. The results will be presented as risk ratio (RR) with 95% confidence interval (CI). The results will be considered significant if CI does not include the value one.

All data processing and analyses were conducted using R statistical software version 4.1.0, 2021–05-18 (R Foundation for Statistical Computing, Vienna, Austria).

If possible, all analysis will be performed for “Practical Course in Systematic Review Technique in Clinical Research” and for “Getting started: Writing your first manuscript for publication” separately.

Primary analyses will be handled with the intention-to-treat approach. The analyses will include all individuals with valid data regardless of they did attend the complete course. Missing data will be handled with multiple imputation [ 28 ] .

Upon reasonable request, public assess will be granted to protocol, datasets analysed during the current study, and statistical code Table 3 .

Oversight, monitoring, and adverse events

This project is coordinated in collaboration between the WHO CC (DEN-62) at the Parker Institute, CAMES, and the PhD School at the Faculty of Health and Medical Sciences, University of Copenhagen. The project leader runs the day-to-day support of the trial. The steering committee of the trial includes principal investigators from WHO CC (DEN-62) and CAMES and the project leader and meets approximately three times a year.

Data monitoring is done on a daily basis by the project leader and controlled by an external independent researcher.

An adverse event is “a harmful and negative outcome that happens when a patient has been provided with medical care” [ 29 ]. Since this trial does not involve patients in medical care, we do not expect adverse events. If participants decline taking part in the course after receiving the information of the course setting, information on reason for declining is sought obtained. If the reason is the setting this can be considered an unintended effect. Information of unintended effects of the online setting (the intervention) will be recorded. Participants are encouraged to contact the project leader with any response to the course in general both during and after the course.

The trial description has been sent to the Scientific Ethical Committee of the Capital Region of Denmark (VEK) (21041907), which assessed it as not necessary to notify and that it could proceed without permission from VEK according to the Danish law and regulation of scientific research. The trial is registered with the Danish Data Protection Agency (Privacy) (P-2022–158). Important protocol modification will be communicated to relevant parties as well as VEK, the Joint Regional Information Security and Clinicaltrials.gov within an as short timeframe as possible.

Dissemination plans

The results (positive, negative, or inconclusive) will be disseminated in educational, scientific, and clinical fora, in international scientific peer-reviewed journals, and clinicaltrials.gov will be updated upon completion of the trial. After scientific publication, the results will be disseminated to the public by the press, social media including the website of the hospital and other organizations – as well as internationally via WHO CC (DEN-62) at the Parker Institute and WHO Europe.

All authors will fulfil the ICMJE recommendations for authorship, and RR will be first author of the articles as a part of her PhD dissertation. Contributors who do not fulfil these recommendations will be offered acknowledgement in the article.

This cluster randomized trial investigates if an onsite setting of a research course for PhD students within the health and medical sciences is different from an online setting. The outcomes measured are learning of research methodology (primary), preference, motivation, and self-efficacy (secondary) on short term and academic achievements (secondary) on long term.

The results of this study will be discussed as follows:

Discussion of primary outcome

Primary outcome will be compared and contrasted with similar studies including recent RCTs and mixed-method studies on online and onsite research methodology courses within health and medical education [ 10 , 11 , 30 ] and for inspiration outside the field [ 31 , 32 ]: Tokalic finds similar outcomes for online and onsite, Martinic finds that the web-based educational intervention improves knowledge, Cheung concludes that the evidence is insufficient to say that the two modes have different learning outcomes, Kofoed finds online setting to have negative impact on learning and Rahimi-Ardabili presents positive self-reported student knowledge. These conflicting results will be discussed in the context of the result on the learning outcome of this study. The literature may change if more relevant studies are published.

Discussion of secondary outcomes

Secondary significant outcomes are compared and contrasted with similar studies.

Limitations, generalizability, bias and strengths

It is a limitation to this study, that an onsite curriculum for a full day is delivered identically online, as this may favour the onsite course due to screen fatigue [ 33 ]. At the same time, it is also a strength that the time schedules are similar in both settings. The offer of coffee, tea, water, and a plain sandwich in the onsite course may better facilitate the possibility for socializing. Another limitation is that the study is performed in Denmark within a specific educational culture, with institutional policies and resources which might affect the outcome and limit generalization to other geographical settings. However, international students are welcome in the class.

In educational interventions it is generally difficult to blind participants and this inherent limitation also applies to this trial [ 11 ]. Thus, the participants are not blinded to their assigned intervention, and neither are the lecturers in the courses. However, the external statistical expert will be blinded when doing the analyses.

We chose to compare in-person onsite setting with a synchronous online setting. Therefore, the online setting cannot be expected to generalize to asynchronous online setting. Asynchronous delivery has in some cases showed positive results and it might be because students could go back and forth through the modules in the interface without time limit [ 11 ].

We will report on all the outcomes defined prior to conducting the study to avoid selective reporting bias.

It is a strength of the study that it seeks to report outcomes within the 1, 2 and 4 levels of the Kirkpatrick conceptual framework, and not solely on level 1. It is also a strength that the study is cluster randomized which will reduce “infections” between the two settings and has an adequate power calculated sample size and looks for a relevant educational difference of 20% between the online and onsite setting.

Perspectives with implications for practice

The results of this study may have implications for the students for which educational setting they choose. Learning and preference results has implications for lecturers, course managers and curriculum developers which setting they should plan for the health and medical education. It may also be of inspiration for teaching and training in other disciplines. From a societal perspective it also has implications because we will know the effect and preferences of online learning in case of a future lock down.

Future research could investigate academic achievements in online and onsite research training on the long run (Kirkpatrick 4); the effect of blended learning versus online or onsite (Kirkpatrick 2); lecturers’ preferences for online and onsite setting within health and medical education (Kirkpatrick 1) and resource use in synchronous and asynchronous online learning (Kirkpatrick 5).

Trial status

This trial collected pilot data from August to September 2021 and opened for inclusion in January 2022. Completion of recruitment is expected in April 2024 and long-term follow-up in April 2026. Protocol version number 1 03.06.2022 with amendments 30.11.2023.

Availability of data and materials

The project leader will have access to the final trial dataset which will be available upon reasonable request. Exception to this is the qualitative raw data that might contain information leading to personal identification.

Abbreviations

Artificial Intelligence

Copenhagen academy for medical education and simulation

Confidence interval

Coronavirus disease

European credit transfer and accumulation system

International committee of medical journal editors

Intrinsic motivation inventory

Multiple choice questionnaire

Doctor of medicine

Masters of sciences

Randomized controlled trial

Scientific ethical committee of the Capital Region of Denmark

WHO Collaborating centre for evidence-based clinical health promotion

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Acknowledgements

We thank the students who make their evaluations available for this trial and MSc (Public Health) Mie Sylow Liljendahl for statistical support.

Open access funding provided by Copenhagen University The Parker Institute, which hosts the WHO CC (DEN-62), receives a core grant from the Oak Foundation (OCAY-18–774-OFIL). The Oak Foundation had no role in the design of the study or in the collection, analysis, and interpretation of the data or in writing the manuscript.

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Contributions

RR, LK and HT have made substantial contributions to the conception and design of the work; RR to the acquisition of data, and RR, LK and HT to the interpretation of data; RR has drafted the work and RR, LK, and HT have substantively revised it AND approved the submitted version AND agreed to be personally accountable for their own contributions as well as ensuring that any questions which relates to the accuracy or integrity of the work are adequately investigated, resolved and documented.

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Correspondence to Rie Raffing .

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Ethics approval and consent to participate.

The Danish National Committee on Health Research Ethics has assessed the study Journal-nr.:21041907 (Date: 21–09-2021) without objections or comments. The study has been approved by The Danish Data Protection Agency Journal-nr.: P-2022–158 (Date: 04.05.2022).

All PhD students participate after informed consent. They can withdraw from the study at any time without explanations or consequences for their education. They will be offered information of the results at study completion. There are no risks for the course participants as the measurements in the course follow routine procedure and they are not affected by the follow up in Google Scholar. However, the 15 min of filling in the forms may be considered inconvenient.

The project will follow the GDPR and the Joint Regional Information Security Policy. Names and ID numbers are stored on a secure and logged server at the Capital Region Denmark to avoid risk of data leak. All outcomes are part of the routine evaluation at the courses, except the follow up for academic achievement by publications and related indexes. However, the publications are publicly available per se.

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Raffing, R., Konge, L. & Tønnesen, H. Learning effect of online versus onsite education in health and medical scholarship – protocol for a cluster randomized trial. BMC Med Educ 24 , 927 (2024). https://doi.org/10.1186/s12909-024-05915-z

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DOI : https://doi.org/10.1186/s12909-024-05915-z

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