This case study provides an account on how we struggled with the coordination of the many activities of a research project in Science Education: managing the project as a whole, collaborating on the literature review, integrating diverse research methods (interviews, classroom observation, survey), analyzing, and reporting. The initial difficulties led us to develop the concept of Digital Research Notebook, a meta-tool and set of workflows to coordinate many of these activities. We will give you practical examples of how we have developed some of the project’s research activities before and after we began using a Digital Research Notebook. We will focus on Collaboration (e.g., writing a paper collaboratively), Project management (e.g., task management), Literature review (e.g., annotating publications collaboratively), Interviews (e.g., collecting audio and handwritten notes in an integrated way), Classroom observation (e.g., a workflow to produce pedagogical graphic novels), and a Survey (e.g., making the dataset and design process open). Our aim is also to present you with scenarios through which you can reflect on the relevance of Digital Research Notebooks and envision its adaptation to your own research project.
By the end of this case, students should be able to
- Understand the practical problems arising from the diversity of activities in a research process
- Develop strategies for collaboration in research and project management through Digital Research Notebooks
- Explore ways to coordinate disparate data and analysis using a Digital Research Notebook
- Reflect on the possibilities of Digital Research Notebooks for your own research project
This case study illustrating the applications of Digital Research Notebooks (DRN) will take as background a research project which aimed to identify the attitudes and expectations attributed by teachers to a new school science space model, the Science Learning Studio (SLS), analyze teaching and learning activities, and inquire about the current situation of instructional, practical, and project-based activities in these new spaces.
The current plan for the modernization of the Portuguese secondary schools’ buildings implemented by Parque Escolar, a public company, established a new school building model prioritizing the schools’ science spaces, modeled on the SLS. Since 2007, this model has already been implemented in 115 schools across the country.
Unlike the Anglo-American model of science learning spaces, formalized in a single laboratory for all classes with daily activities of observation and/or experimentation, the Portuguese previous model included both traditional classrooms for lectures and laboratories for practical work.
This bipartite model contrasts with the new model, in line with the learning studios and classrooms/environments for active learning in scientific subjects (see, for example, Robert Beichner’s Student-Centered Activities for Large Enrollment Undergraduate Programs [SCALE-UP] project to get an idea: http://scaleup.ncsu.edu/), a hybrid space to support instruction, practical work, peer-instruction, and diverse teaching and learning activities.
For this research project, we designed a path of mixed methods to approach the research questions, which began with case studies involving classroom observation, interviews, and later a survey to teachers using these new spaces. It became evident early on in the research process that trying to connect such diverse capture methods and data analysis would be a complex task. Besides this methodological issue, we felt that our efforts to coordinate the project as a whole could be improved if we used adequate project management and collaboration tools.
We looked into the literature that could help us map all the activities of our research process and start to address these challenges in a more structured and consistent way. From Miles and Huberman, we understood that a qualitative research process may involve the following:
- Reviewing the literature;
- Generating data;
- Storing, protecting, and managing data;
- Data linking;
- Analyzing content;
- Data displaying;
- Graphic mapping;
- Research project managing.
One possible way forward would be to use a QDAS (Qualitative Data Analysis Software) package. Despite the focus on data analysis, these highly advanced software are evolving to provide support to many of the above activities. We explored some of these with collaboration and project management in mind, but the learning curve was high for some team members, its analytical features were too high-end, the costs were significant, and there was a need for easier integration of the software in the diversity of individual working processes and tools (Table 1). If QDAS excelled in the central analytical phase of a research project, they still did not provide us with the best support for all the stages and activities of the research project.
|Table 1. Research activities and digital tools used before developing the concept of Digital Research Notebook.|
Google Drive and Skype
Reviewing the literature, generating data and memoing
Adobe Acrobat Professional, Evernote, Microsoft OneNote and Mekentosj Papers
Storing, protecting and managing data
Dropbox, Bittorrent Sync and Synctoy
Transcribing, analyzing, coding and data linking
NVivo, MAXQDA, and ATLAS.ti
Data linking and graphic mapping
VUE, Mural, and NVivo
Adobe InDesign, Google Drive, and Microsoft Word
Folders, Google Tasks, Trello, and Google Calendar
With this in mind, we began developing the concept of DRN, not as a way of eliminating this diversity of tools and processes or replacing QDAS for deep analytical purposes but to provide a common ground that supported our research activities as a whole.
We engaged in a search for platforms that could provide the coordination we were lacking. We tried several project management and collaborative platforms, collaborative design and innovation platforms, mostly business-oriented, but remained unsatisfied. We ended up resorting to a tool that we had already been using for several research projects in a simpler way—Microsoft OneNote.
OneNote is usually portrayed as a digital notebook for general audiences. It has meanwhile encountered several applications in education, but not in qualitative or mixed-methods research, as far as we know. We had used OneNote for research notetaking, memoing, and literature reviewing for more than 8 years. Facing difficulties in coordinating our research practices and supported by the research literature on software for qualitative research (e.g., the work of Paulus, Lester, Dempster, Silver, and Lewins), we developed procedures and templates which made OneNote a useful digital tool for our entire research process. We named these notebooks tailored to our research DRN.
In the following sections, we will describe several practical issues that arose in a Science Education research project and on how DRN helped us deal with the myriad of activities involved in the entire research process:
- Collaboration (e.g., writing a paper collaboratively);
- Project and data management (e.g., task management);
- Literature review (e.g., annotating publications collaboratively);
- Field work and data analysis;
- Interviews (e.g., collecting audio and handwritten notes in an integrated way);
- Classroom observation (e.g., a workflow to produce pedagogical graphic novels);
- Survey (e.g., making the dataset and design process open).
We will describe and analyze an example of collaboration in our research project, writing a paper collaboratively, by focusing on its practical features. We will try to illustrate a scenario of how we did some of the collaborative writing in previous projects, the challenges that arose, and how we developed the DRN to find better ways of working in the current project.
In the process of writing a paper, we would begin by discussing ideas, mentioning some articles, and so on and jotting down some notes about it. We would then write a provisional index of topics and sort which parts each person would write. This was usually done in a meeting and the draft index would be emailed to the group.
Using the DRN allowed us to better explore these first stages of writing. For a creative brainstorming, we developed a Canvas template (Figure 1) with the possibility of writing anywhere, very similar to what can be done with post-its on a wall.
This made a considerable difference in sparking creativity. It was more versatile than just playing with post-its, because it allowed us to place text, photos, screen clips, videos, drawings, and files all in the same place, zooming in to certain areas of the canvas to focus on a theme or zooming out to get a bird’s-eye view of the entire canvas. We could also move these elements in the Canvas, connect them, sort them, and so on and thus explore our ideas more grounded in data. From an initial chaotic display of things, we ended up with an organized collage of data. This made easier to create a provisional index for writing and have available information we could readily use to develop the paper. And there was no need to email the provisional index as it was done in a notebook page shared between the authors.
Before using a DRN, on receiving the draft index by email, we would then work individually in a word processor of choice and use our own personal way of writing. We would add pieces of previous texts, write and rewrite new text, add citations, notes on sources, comments, and so on. We tried to keep a close connection between what we were writing and the sources of information that inspired that piece of text or worked as evidence. We would usually make a note to direct us to it, in the form of a link to a file or source, but this was very cumbersome to make and follow.
Writing in the DRN solved the problem of relating the writing with the actual sources, making it more grounded (Figure 2). Besides writing, in the DRN pages, we could insert any type of file (PDF, Word, Excel, PowerPoint, photos, audio, video, etc.). This meant that at the end of any paragraph, we could have the actual source or a link to it in another notebook page.
This linking ability between text and files extended also to text paragraphs (Figure 3). With a few clicks, we could make a link from one paragraph to another.
We now had the ability to better grasp, compare, and analyze different pieces of texts and make our writing more creative and grounded.
Before using DRN, when the individual writing of each topic had evolved and was clear enough, we would put our writings together in a single common file (usually in Word) and share it between authors.
We would then read each other’s work and use the review features (comments, track changes, and versions) to make suggestions, corrections, and so on. The file would be sent back and forth by email, and if this became too frequent, we would place the file in a shared cloud drive (Dropbox, Google drive). We would then email each other or use a VoIP application (Skype) to report the status of the document or to request comments or follow-up.
When we were together, we could write on the same piece of text while discussing it. In an online meeting, this would be done using the sharing screen feature. Sometimes, when we really needed to advance the text faster, we would use Google Docs to edit the text at the same time.
With the DRN, our work became collaborative from the start. Instead of working individually in separate Word files, each of us worked in different pages in the same notebook section. The pages in the DRN are organized similarly to a pen and paper notebook (Figure 4). In the Output section, in the page group dedicated to the paper, we would have a page for each topic (and subpages, if needed). Each page would initially be attributed to an author and later reviewed by everyone.
Having all the writing in the same place and everyone with easy access to it made a difference in the way we communicated and wrote. The ability to quickly skim through each other’s texts also let us have a bird’s-eye view of its progress.
When we needed to write collectively in a single page, OneNote had a set of unique features (Figure 5) that supported our collaborative writing:
- Turning the title of every page recently edited by other authors to bold;
- Highlighting all new edits in a page with a green background;
- Identifying the last author of each paragraph of text, through a colored ribbon on its right side;
- Searching for recent edits, by author, in a certain page or section;
- Using visual tags (like To Do) in paragraphs to comment, ask questions, and so on.
All this would let us know about recent edits, which part of the text was written by whom, easily follow-up changes, or comment directly with the author.
We would work on the text in the DRN until it was ready for final editing. For this final stage, we would export the notebook pages to Word to apply formatting, count words, number pages, insert references, and so on. When working on the final version of the Word file, we would place it in OneDrive to work synchronously and online on it. We would also insert the file in a notebook page, to have easy access and to archive the final version.
In our previous research activities, project management was usually done informally, without much effort put into it. We were confronted with a series of difficulties while trying to manage the project collectively and as a whole. Through the DRN, we tried to find solutions to task and time management, logging, auditing, and analytical and institutional data management.
In project meetings, we would decide on next steps and attribute tasks to each colleague. We would then jot down a few points or make a meeting minute. The minute would later be shared by email with everyone. Sometimes more detailed lists would be done individually by the person in charge of the task to better organize it and control its development.
If the tasks demanded deeper collaboration, we would write To Do lists in a shared Evernote notebook. Though useful, this would usually become an “infinite” list full of leftover To Do’s.
The DRN opened up the possibility for a finer grain management of the project. The way we defined tasks became clearer and better grounded on the actual work we were doing. In the DRN, tasks could be written as checkboxes in the actual page or piece of text where they originated (Figure 6). We did not have to move to a Tasks’ page to write them down, losing focus or separating the context from the task.
Besides the To Do checkbox tag, we developed a simple collection of visual tags that let us leave notes to oneself and others to manage our activities. We called them processual tags, as they facilitated the moving forward of the research processes: to-do, to-think, important, comment, common, and so on. This tagging was also made in context. Following up tasks became simple as the DRN was able to harvest all the tags from a page, section, or notebook, through a “Find tags” feature (Figure 7). This gave us a bird’s-eye view of what was significant and had to be acted upon. We could even generate summary reports of the tags, by author, type, or date, facilitating the way we managed our tasks.
For time management purposes, such as organizing meetings, defining deadlines, or scheduling field work, we started using a shared Google Calendar or Doodle.
With the DRN we could add a time tag to any task, like today, tomorrow, or specific to a date and time. Timed tasks were automatically integrated with Outlook tasks and could be viewed in the application. We could then add reminders to these tasks to get, for example, alerts on our mobile phones.
For the team to follow what was happening in the project, we tried to integrate the tasks with a calendar (Outlook or Gmail) to generate a kind of log of all activities. This was something that was never easy to achieve, and the detailing of so many small tasks was not helpful.
To solve this, in the DRN we decided to develop a Logger (Figure 8), a calendar-like section, where we collectively added the main themes being worked on that week, with direct links to the section or pages in progress.
We also thought of maintaining a collective Research journal (Figure 9) where we would periodically collect the significant moments of the research: significant readings, data, insights, reflections, events, and so on. To have reflective purposes, the journal was multimedia and had links to the information sources elsewhere in the notebook. Any participant could edit or comment it. We developed a Graphic Novel template to collect information from other parts of the notebook to make this journal easy to follow. This format could also be useful in showing other stakeholders how the research process was going.
These two features, the Logger and the Research journal, linked to the content of research, could, we believed, make our research process more open and our work more auditable and ethical.
Before developing the DRN, we captured the many data files (interviews, classroom observations, etc.) with cameras, audio recorders, and handwritten field notes on paper. Photos, audio and video files were then stored locally and organized into folders. To share these local files, we used cloud services (Dropbox for non-sensitive documents and Bittorrent Sync for sensitive data that required encryption). Such dispersion in the data hindered our capacity for analysis, mostly when we wanted to work together on it.
Resorting to the DRN changed the way we captured data. OneNote allowed us to capture directly into a page: photos, audio, video, or external files. We were able to organize them in custom pages, which we called Collectors (Figure 10), adding information on capture contexts, metadata, summaries, and so on.
We also had to manage general information related to the research project, such as emails, grant application documents, acceptance terms, regulations, and accounting. These files would be previously organized in folders or email applications and disconnected from the research data.
With the DRN we put disparate information together and easily accessible. The previous problem of managing email information of common interest to the project was easily solved through the ability of Outlook to send emails directly to OneNote. This made possible the creation of a repository of relevant emails.
All the information, now in one place, could be easily shared and collectively organized, facilitating search and linking, fostering analysis at a deeper level. General information (Figure 11) was closer to the data and analysis, making the management of the project as a whole easier when we needed to write reports, ethical approvals, and so on.
The literature we were interested for this project was quite diverse. Some was acquired in paper or digital, and other was available in online repositories or came from personal collections. We made the effort of scanning some of the publications with optical character recognition (OCR) (Acrobat Professional XI) and defining a common format for our digital library (PDF), later organized in a reference management software (Papers). We could make full content searches of all the publications and comment and annotate them.
We started developing Library sections in our DRN for specific themes. The sections were organized by themes and in Publication Collector pages (Figure 12). We added the PDF file of the publication to each page, along with some metadata and a summary review. The files in the notebook could still be shared with the reference management software if they were imported from a common cloud drive (like OneDrive or Dropbox), keeping the access to the latest version of the file.
Most reference managers allow annotations in PDF, but relating texts excerpts within and between papers or moving your annotations for further editing is more demanding. This turns analysis into a cumbersome process. If you add collaboration to this, the problem grows exponentially.
This led us to develop a workflow to make collaborative annotations, linking and tagging/coding that made possible a more in-depth analysis of the literature.
With the PDF opened from its Publication Collector, we would place it side by side with a Literature Review Matrix template (Figure 13)—a series of columns with card-like cells—and then copy excerpts from the PDF and paste them in the cards. In PDFs protected from copy/paste, we would use the OneNote screen clipping tool and cut and paste the screen region of the paragraph we were interested in collecting, and then apply the feature of text recognition in images.
What OneNote offered, more than extracting and compiling texts from publications in an organized way, was the possibility of using on the selected texts a set of manipulation tools (highlighting, outlining, drawing upon) and, most of all, the ability to link and tag paragraphs.
Linking paragraphs of text within the same page or between any paragraph in any other section in the notebook (Figure 14) proved to be a very grounded and in-depth analytical procedure, facilitating comparison of sources, prioritizing, theming, and so on.
In the DRN, we also created custom tags, like codes, that would be applied at a paragraph level, similar, though simpler, to coding in QDAS. This allowed us to make a tag search and extract the relevant texts across our entire library, along with the comments made on them. We could also generate summary pages of that search (Figure 15). Manipulating text in this way offered deeper and better grounded insights. When we needed further detailed analysis, we would resort to QDAS, but the balance between effort and depth in the DRN was adequate for many of our analytical questions.
Another method used in this research project was a walkthrough interview schedule that provided a spatial agenda for participants to respond to. We wanted to elicit the practices associated with the key design elements of the SLS (Figure 16) and contrast them with the idealized model. This meant that the interviews took place in the actual studios, where the interviewer and interviewee could directly interact with space and objects. The interviewer used a visual checklist that defined a route through the studios, with some key stops where questions would be made.
This kind of interview meant that the interviewer and interviewee were constantly moving in both the studio and prep room, exploring, changing the space, or demoing some applications, while
- Recording the interview (audio);
- Taking photos;
- Taking handwritten notes.
The pilot interviews and photos were recorded with a mobile device and handwritten notes were taken in a paper notebook.
The immediate problem arising from this was the difficulty in linking all these data. The digital files were usually stored in a folder by file type and interview date, if in a digital format, or linearly in the field notebook on paper, with post-its acting as separators. So, how to make them manipulable in a common working space for research purposes?
We developed a Handwriting template in our DRN that could be used with a tablet and pen by the interviewer during the interview process. The interview schedule was at hand in the same section to help the process. In this template, we would directly record the audio of the interview, include the photos taken, and handwrite our notes. The information was in this way kept all in one place and usefully synced (Figure 17). This meant that when we played the audio recording, the handwritten note taken at the time of the capture would become highlighted (and vice versa).
To recover some old interview data, we devised a workflow to easily scan notebooks with a mobile device, using Office Lens, and then add them to the DRN. We also tested a smart pen that writes in plain paper but can send all the text and drawing to OneNote. All the digital handwriting could be accurately converted to text in the application (Figure 18).
Although working with paper and digital was quite difficult at the start of the process, mixing paper and digital workflows through DRN became quite manageable.
OneNote provides a basic interface to support transcribing of audio or video interviews. We can play the recording forward and backward, jump to a specific time tag, and in this way transcribe the entire interview. We can later sync the transcription with the audio by simply adding paragraphs to the text in the moment we were listening to it. With this syncing in place, when we played the audio again, the corresponding text would be highlighted, and if we played the text (a small play button is added to each paragraph), we could listen to the matching audio (Figure 19). This made it much easier to quickly access the context of the talk while doing analytical work.
From this transcription, we could apply all the features of OneNote such as tagging, searching, and linking, providing more opportunities to ground our overall research work.
The goal of classroom observations in our project was to analyze activities using a Science Learning Studio Activity Analysis Methodology. In this section, we will show you how we collected multimedia data in a DRN in an integrated way, processing it and finally generating a Pedagogical Graphic Novel, a kind of storyboard of classroom activities.
In the pilot phase of the project, we began generating data from classrooms using a camera to record video and take some photos, and registering observation notes using Evernote.
A significant problem with this data collection process was the difficulty in syncing the available data in a common timeline without some considerable effort. We had photos in one folder, video in another, and notes yet in another place. Handling large video files and doing collaborative analysis were also very demanding.
Our vision for classroom observation methods was that they could be a meaningful process not only to researchers but also to students and teachers. For pedagogical and professional development purposes, we also thought of classroom observation as an opportunity to produce shareable outputs of real classroom practice. To address all these challenges, we designed a participatory workflow for producing Pedagogical Graphic Novels.
From our previous experiences using storyboards to capture classroom activity, we decided to produce a graphical output of the classroom observation, to easily communicate classroom activity, in both paper and digital formats. We revised the storyboard concept and reframed it as Pedagogical Graphic Novel.
We still needed to design a workflow easy enough to sync the several data types (notes, photos, audio/video, and files), allow analysis, and generate a flexible output, keeping its participatory and collaborative nature.
The first step was to provide one student with a tablet with Internet access and instruct him or her to capture classroom activity, by taking photos and writing captions on a DRN page (Figure 20). We were connected to this same page in another device, recording classroom audio.
In this way, we could follow the student’s capture in real-time and give him or her just-in-time feedback on the relevance and quality of the capture.
By the end of the class, we would review the photo capture and captions made by the student, cropping images in the DRN to focus its key aspects and composing them into a Graphic Novel template.
Finally, we would sync the audio with the captions so that when we played the audio, the text would be highlighted and vice versa.
We also created links from parts of the text to data collected in other formats (e.g., PDF files or PowerPoints used in class), or transcribed certain interactions, providing more detail to the graphic novel.
This first draft of the Pedagogical Graphic Novel (Figure 21) was then edited with the teacher. Besides correcting it, we discussed particular aspects of the activity relevant to the research project and identified the issues that could be raised when discussing the novel with the class.
In the class following the recorded one, we would project the graphic novel in class and analyze and review the activity collectively, with the vignettes framing the discussion. During the discussion, more changes were done to the novel.
This workflow finished with publishing the graphic novel in PDF and paper formats. For that, we developed a template in OneNote formatted to print in an A3 paper size in landscape mode. With one click, we exported it to Word, where we added page breaks, page numbers, or headers, and then exported the final result to PDF or print. The novel had as authors the student, the teacher, and the researchers.
In this section, we will describe how the survey in the research project was developed, illustrated, and shared in a DRN.
We wanted to integrate themes from several other surveys to have a reference to which to compare some of our results. We also needed to link our current research, namely, the case studies, to the survey design.
We began by using Word to prepare an early draft and to start iterating versions. We pasted several questions from different sources, our own ideas from the research questions, and tried several structures with heading styles. This file would then be shared between the team, usually in a cloud service, and commented and worked upon.
We felt some difficulties in dealing with the linear flow of text of a word processor in this conceptual stage, so we started using DRN to compare and sort interesting questions from previous surveys. We copy/pasted them from PDF into a Matrix template (Figure 22) designed for this end, in which they could be easily put side by side, zoomed in and out, and combined with other modalities other than text. We could also have different OneNote pages opened side by side which allowed a much easier comparison between questions and the Matrix with the overall design ideas.
We began iterating drafts in OneNote using the outline feature to comment on each question. This made collaboration easy between the team to get to the final version before validation.
We planned a visual approach to the survey, with illustrations and photos of classroom activity that could help respondents to reflect on their own practices.
Our survey was applied to teachers from 106 schools intervened by Parque Escolar. The questions were organized in five categories: (1) Basic data on the respondents, (2) Use of the new SLS, (3) Teaching and learning activities in the new SLS, (4) Experience during the intervention by Parque Escolar, and (5) Detailed data on the respondents.
Photos from graphic novels were the obvious content for Section 3 of the survey. But in Section 2, we wanted to show diverse situations of the SLS in use so that respondents could have a concrete situation to respond to.
Initially, we made several experiments with a three-dimensional (3D) model of the new SLS in Google Sketchup. The goal was to assess the practicality of a workflow to create short illustrated activities in the SLS. The initial process was somewhat complex— - define the framing in Sketchup and export pictures, print them in paper, draw upon characters and objects, and scan the result (Figure 23). This was not practical.
So we began some experiments using digital ink in OneNote to create simple characters and objects (Figure 24), which would then be overlaid on the Sketchup frames. This proved to be a simple workflow. We could also reuse characters in other illustrations.
From the start, we wanted to make the raw data and the results from this survey available to both respondents and the wider research community. Our initial strategy was to use the survey software features to share the results automatically with the respondents and, later, to make the data and results available in an open repository.
We used SurveyGizmo to manage the email campaign, deliver the online survey, and report on the results. This tool had the possibility to share with respondents both their individual responses and the results’ report.
For the remaining stakeholders, we used the DRN to share the dataset (embedded as an Excel file) (Figure 25), the data analysis reports (PDF), the outputs (as papers), and the development process, from survey design to validation and implementation (a set of OneNote pages).
In this case study, we went through the application of a new concept, the DRN, to a Science Education research project. We have tried to show you some concrete dilemmas in our everyday research lives and how DRNs helped us solve some of them. Looking beyond the technical details and paraphernalia, the impact of DRNs we most value in our research was that it made many of the activities more productive and insightful, while fostering in practice our values of doing research in a collaborative, participatory, grounded, reflective, and open way.
Our vision of an open science is one that goes beyond communicating and sharing only the research results. Making accessible the processes of research is fundamental for the quality, ethics, and responsibility of Research in Society. We believe that DRNs can be a way of achieving these ends.
- Go to http://onenoteinresearch.com/explore-a-demo/ and download a demo of a Digital Research Notebook (DRN). Explore the notebook which illustrates the first week of a research project. After becoming acquainted with what can be done with it and how you might do it, try to work with your own information and construct a DRN for your research. Here are some challenges to get you started:
- Organize your DRN by sections that represent your research design: for example, “Library,” “Field data,” and “Institutional.”
- Extract text from relevant articles from your Library and paste it in a page. Now try to explore the “link to paragraph” function to connect paragraphs of text in different pages.
- Organize part of your bibliography in the Library section using the library collector template.
- Take meeting notes at the same time you record its audio. Explore the syncing feature between audio and notes.
- Share your notebook and write a text synchronously and asynchronously with a colleague to get acquainted with the collaborative features of OneNote.
- Customize a couple of tags to organize your content. Use the Find tags feature and generate a summary report.
- Install OneNote in your mobile phone or tablet, open the DRN and take photos, capture audio, or take notes (handwritten or not) on the go.
- What practical problems do you encounter in coordinating the diversity of activities in your research projects?
- What possibilities do you envision in DRNs applied to your own research?
- Action, participatory, collaborative, open research … Which one best fits your views on research? Can the DRNs help you foster any of these?
The project “Attitudes, expectations and practices in the Portuguese secondary schools’ science laboratories” (PTDC/MHC-CED/5116/2012) was funded by national funds through FCT—Fundação para a Ciência e a Tecnologia (the national funding agency for science, research and technology). The principal investigator was Professor Vitor Duarte Teodoro, from Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Portugal.