Monthly Archives: April 2016

PDF pen for Mac

Screen Shot 2016-04-12 at 12.23.50 PM PDF-Pen is available in the App Store.

It seems to be a must have tool for Academics because:

  • It does Optical Character Recognition, therefore pictures of text can be converted into words you can use and proofread for accuracy.
  • PDF’s can be converted into Word format (.dc and .dox) for easy editing and sharing.
  • The text in the PDF can be selected and edited, therefore editing a PDF on your Mac is easier than ever before.
  • Documents can be signed by dragging and dropping an image of a signature into a document, or by using the mouse or trackpad to scribble your signature. Therefore, documents can be signed, sealed, and delivered with no fax machine needed.
  • Documents can be hared in iCloud Drive or Dropbox for seamless editing with the PDF pen for iPad and iPhone.
  • For iCloud, the App Store version is needed.


Use the PDF pen to:

  • sign forms
  • insert page numbers
  • highlight and underscore text
  • add text, images and signatures to PDF
  • move, resize, copy and delete images in the original PDF
  • copy and paste rich text, including columns
  • use on scanned documents and pages
  • scan directly from Image capture scanners
  • adjust resolution, colour depth, contrasts, skew, and sixe of an image
  • sensitive for popup-menus
  • edit quickly
  • print notes and comments with or without original text
  • print list of annotations along with the document
  • add (and print) notes and comments
  • fill out and sign interactive PDFs
  • apply business related stamps
  • reorder and delete pages
  • combine PDFs
  • automate manipulations
  • save PDFs to Evernote

Redact personal information by:

  • redact or erase text
  • password protect documents

For now, I have downloaded the FREE TRIAL version from the developer’s website. There is no time frame, they just add a logo to the saved documents. Will add to wish list if I love this app.

Mendeley 12: How to use different colours for annotations

On the 31st of March 2016 Mendeley improved its annotation affordance, by adding a rainbow of colours that can be used to annotate documents and papers. In fact, users can use 8 colours for annotation purposes.

To use different colours, follow these steps:

  • Click on the icon to open the document in Mendeley

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  • Click on the coloured dot in the top menu to open the box

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  • The colour of the dot changes to the preferred colour
  • Click on the highlight icon (top menu)

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  • Mark the text you want to highlight and it is highlighted

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  • to add a comment, click on the comment icon (top menu)

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  • the comments will be in the same colour than the highlighted text

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  • Different colours can be used in the same document

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So, how will you use this affordance of Mendeley? I can suggest two ideas:

  • Use it for your own research to quickly identify various ideas you have identified – eg, methods in green, concepts in blue, etc.
  • Allocate a colour to a team member to easily find the text highlighted by a certain team member when you use the group function.

Please like if you found these instructions helpful or comment to suggest improvements.  Have fun!

Mendeley 11 – How to get access to a group in Mendeley online

When a group was created for collaborative purposes, the following steps can be followed to participate in the group:

Instructions for online access to a group

  • Click on Groups (top menu)

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  • Click on the name of the group

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  • The overview of the group will open (see top menu)

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  • Please note: It differs from the window that opens in the desktop application:
    • menu is on left hand side of screen
    • and refer to papers not documents

The papers/documents view screen also differ from the desktop application

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  • Click on members to view the members of the group

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  • To invite members, add email addresses in the box provided

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  • To manage invitations, click on the blue button (right)

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  • If links are blue, the invitee is a Mendeley user
  • If links are black, the invitee is not yet a member of Mendeley
  • This group is owned by me, but the settings can be edited so that somebody else can own it

Screen Shot 2016-03-19 at 10.33.03 PM

  • To edit a group, click on the Edit settings button (see image above)

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Have fun – I believe this feature can improve collaboration between researchers and faculty members.

Please like if found usable or leave a comment to suggest improvements.

Mendeley 10 – How to get access to a group in Mendeley desktop

When a group was created for collaborative purposes, the following steps can be followed to participate in the group:

Instructions for Desktop access to a group

  • Click on Groups (left menu)
  • Click on the name of the group

Screen Shot 2016-03-19 at 10.27.02 PM

  • The overview of the group will open (see top menu)

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  • Click on documents to see the shared documents

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  • Click on members to view the members of the group

Screen Shot 2016-03-19 at 10.33.29 PM

  • To invite members, add email addresses in the box provided

Screen Shot 2016-03-19 at 10.37.15 PM

  • To manage invitations, click on the blue button (right)

Screen Shot 2016-03-19 at 10.35.26 PM

  • If links are blue, the invitee is a Mendeley user
  • If links are black, the invitee is not yet a member of Mendeley
  • This group is owned by me, but the settings can be edited so that somebody else can own it

Screen Shot 2016-03-19 at 10.33.03 PM

  • To edit a group, click on the Edit settings button (see image above)

Screen Shot 2016-03-19 at 10.40.18 PM

Have fun – I believe this feature can improve collaboration between researchers and faculty members.

Please like if found usable or leave a comment to suggest improvements.

Common errors hindering ethical clearance

In this post, I will list common errors that can hinder ethical clearance.

Type of research and researcher’s details

  • Risk category not correctly identified: rather indicate a higher than lower risk when humans are involved: high risk refers to studies where teenage pregnancy, sexual abuse, cerebral palsy, dyslexia, epilepsy, etc is investigated. Therefore most of the research conducted with regard to teaching and learning will fall under category 3 or lower. If humans are involved, it cannot be category 1.
  • Title of project is not consistent used throughout the document
  • Conflict of interest not recognised: If the researcher is also the lecturer, conflict of interest need to be addressed. How will the lecturer deal with the situation to safeguard the participants
  • Research questions, problem statement, and subquestions, purpose and anticipated outcomes of the research not addressed during description of the background to the study
  • Sample size is not clearly described
  • criteria for participant selection is not described
  • data collection instruments for focus group interviews, observation, interviews, questionnaires and online surveys are not attached to the forms when applying for ethical clearance
  • each instrument not on separate page and numbered in a logic sequence

Obtaining permission, consent and assent

  • procedures followed to obtain permission to conduct research are not listed
  • researcher did not describe how permission, consent and assent will be obtained
  • When children younger than 18 are involved, assent from child as well as consent from the parents/caretakers need to be obtained
  • example letters to be used to ask permission, consent and assent are not attached to the forms.
  • letters are signed, which indicate that the assent, consent and permission were obtained prior to the request for ethical clearance. In such a case ethical clearance will be refused as the request will be regarded as retrospective

Requirements with regard to letters to ask permission, assent and concent

  • title of research not provided
  • name of researcher and contact details not provided
  • purpose not indicated
  • did not indicate time/effort etc required from students – how long will the interview be?
  • did not indicate that videos/photographs will be taken
  • did not describe how identity of participants will be protected when images and videos are used
  • did not tell the participants that they can withdraw from study
  • did not tell them that participation is voluntarily – most important when using own students as participants


  • All checklists not completed
  • If a yes or no is required, it is not indicated for all listed issues
  • Did not use n/a if not applicable

CV’s of all researchers requiring ethical clearance

  • CV’s not attached
  • CV’s do not indicate why this person will be knowledgable to conduct the research

Declaration form

  • declaration form not signed
  • no declaration form attached

Please comment if you can identify issues I have not addressed, this will help to provide complete guidelines for completing ethical clearance requests.

Ethical issues that need to be addressed

Various ethical issues need to be addressed during a research project. In order to address these issues, researchers have to:

  1. recognise issues of respect, fairness, and dignity for all those who are involved in or affected by the research (Connolly 2003:27, Sullivan and Cain 2004:603).
  2. provide a thorough description of the research process so that potential participants have the information needed to make an informed, voluntarily consent (or assent in the case of minors, or provide permission in the case of institutions/organisations) (Connolly 2003:14-15, Cottingham & Jansen 2005:4, Duma, Khanyil and Daniels 2009:53).
  3. ensure the safety of the participants (Cottingham & Jansen 2005:3, Duma, Khanyil and Daniels 2009:53).
  4. honour and maintain anonymity, confidentiality and privacy (Connolly 2003:23, Duma, Khanyil and Daniels 2009:53, Ellsberg & Heise 2005:53).
  5. ensure beneficence, by minimising risks and maximising benefits of a study (Connolly 2003:23, Duma, Khanyil and Daniels 2009:53)/
  6. take precautions to avoid inadvertent reinforcement of negative social stereotypes concerning particular groups, unfair exploitation of vulnerable research participants, and to ensure that no distress is caused to people who have suffered traumatic events (Flaskerud & Winslow 1998, Sullivan & Cain 2004).
  7. protect the physical and psychological well-being of their participants in order to ensure that participation do not result in in distressing ethical misfortunes (Duma et al 2009).
  8. provide arrangements for support, if needed, before, during, and after the research for participants who have experienced traumatic events (I believe failure falls under this issue) (Cambell & Wasco 2005).
  9. make appropriate appropriate support mechanisms for researchers and participants alike, including briefing sessions and the opportunity to meet with the researcher (Connolly 2003:27).
  10. ensure that information about the research is ommunicated in a way that is meaningful to the individuals concerned (Aitken, Gallagher and Madronio 2003:340-341)
  11. gain written and verbal consent (assent if younger than 18 with permission from parents, caretakers) (Connolly 20013:30)
  12. inform participants prior to the research of sensitive questions that will be asked during interviews, as well as the procedures thereof ((Ellsberg & Heise 2005:35)
  13. guarantee confidentiality, anonymity and privacy (Ellsberg & Heise 2005:35)
  14. be aware of cultural differences that may exist between the researcher and the participants (Duma, Khanyil & Daniels 2009:53)
  15. ensure that, if an interpreter is involved, that the interpreter speak the same dialect as the participant (Bot 2005:176-179)
  16. ensure that interpreters receive training on documents, topics, background, objectives and purpose of the study, length of the interviews and procedures for maintaining confidentiality (Bot 2005:176-179)
  17. put strategies in place to deal with the participants’ immediate and ongoing emotional needs, and where necessary, refer them in the case of a crisis to relevant support services (Connolly 2003:34)
  18. locate and contact vulnerable research participants without endangering their safety (Duma, Khanyil & Daniels 2009:56-57)
  19. ensure that interviews will be conducted in a private and safe settings (Connolly 2003:34).
  20. I will add as I find reference to more issues …..

Socio-critical principles to guide ethical decision-making

The need for ethical desicion-making should not be seen as regulatory hurdles that need to be jumped through at the beginning of the research process in order to address concepts such as vulnerability, harm, respect for persons, and beneficiaries are addressed, but rather as a process that ground ethical inquiry (Markham and Buchanan 2012:5). “Harm” is defined contextually, therefore ethical principles are more likely to be understood inductively than applied universally (Markham and Buchanan 2012:4).

Rather than one-size-fits-all pronouncements, ethical decision making is best approached through the application of practical judgment attentive to specific contexts (Markham and Buchanan 2012:4). Although one set of norms, values, principles and usual practices can be seen as legitimately applied to the issue(s) involved, it becomes difficult to make judgements as to which sets apply, especially if one set conflicts with another in one or other way (Markham and Buchanan 2012:5). The need for guidelines during the research process is emphasised by the fact that learning Analytics increase an institution’s scrutiny of student data related to ownership of the data and student privacy. Therefore, it is necessary to understand the opportunities and ethical challenges of learning analytics research.

Learning Analytics is one of the key emerging trends in higher education, but a number of issues need to be addressed (Siemens 2011). One of the issues relates to ethical decision making (Markham and Buchanan 2012:5). Therefore researchers are forced to determine which is relevant in a specific context or at particular junctures during the research process (Markham and Buchanan 2012:5). Ethical decision making is a deliberative process, and researchers should consult as many people and resources as possible in this process, including fellow researchers, people participating in or familiar with contexts/sites being studied, research review boards, ethics guidelines, published scholarship (within one’s discipline but also in other disciplines), and, where applicable, legal precedent (Markham and Buchanan 2012:5). Markham and Buchanan (2012:5) agues that we need guidelines rather than a code of practice so that ethical research can remeain flexible, responsive to diverse contexts, and adaptable to continually changing etchnologies. In this regard,Ethical issues may arise and need to be addressed during all steps of the research process, from planning, to research conduct, to publication and dissemination (Markham and Buchanan 2012:5). According to Slade and Prinsloo (2013:2) ethical decision-making depend on a range of ideological assumptions and epistemologies.

From a social-critical perspective, the role of power, the impact of surveillance, the need for transparency and an acknowledgement that the student identity is a transient, temporal and context-bound construct is regarded as important (Slade and Prinsloo 2013:2). Each of these affects the scope and definition of the ethical use of information collected, therefore Slade and Prinsloo (2013:2) proposed six principles as a framework for a number of considerations to higher education institutions to address ethical issues in learning analytics and challenges in context-dependent and appropriate ways.  Slade and Prinsloo (2013) proposed six principles that should serve as guidelines for higher education institutions using or planning to use data.

Principle 1: Learning analytics as moral practice

Learning analytics should not only focus on what is effective, but also aim to provide relevant pinters to decide what is appropriate and morally necessary (Slade and Prinsloo 2013:12). According to Slade and Prinsloo (2013:12) education is primarily a moral practice, not a causal one. Therefore learning analytics should focus primarily as a moral practice resulting in understanding rather than measuring (Reeves 2011).

All digital information at some point involve individual persons therefore, considerations of principles related to research on human subjects may be necessary even if it is not immediately apparent how and where persons will be involved in the research (Markham and Buchanan 2012:4). Learning analytics should do much more than contributing to a data-driven university or leading to a world where data drive our actions.

Principle 2: Students as agents

Principle 3: Student identity and performance as temporal dynamic constructs

Principle 4: Student success is a complex and multidimensional phenomenon

One of the benefits of learning analytics is to contribute to a better understanding of student demographics and behaviours (Bichel 2012), but it is important to see student success as the results of

Principle 5: Transparency (Slade and Prinsloo 2013:14) provided the following guidelines:

  • State a clear purpose for using the data
  • Under which conditions will the data be collected?
  • Who will have access to the data?
  • What measures will be taken to protect the identity of individuals?

Please note: Markham and Buchanan (2012) argues that participation in public online forums do not provide blanket permission for using data. Therefore, the greater the vulnerability of the community, author, participant, the greater the obligation of the researcher to protect the community, author or participant. Therefore, higher education have an obligation to protect student data on the institutional LMS, and also to inform students of possible risks when teaching and learning occurs outside the boundaries of institutional jurisdiction (Slade and Prinsloo 2013:14).

Principle 6: Higher education cannot afford not to use data

The triggers for adopting learning analytics depend on the main purpose for collecting data, whether it is to improve profit or learner results (Slade and Prinsloo 2013:14). Institutions should be able to use the data to better understand and then engage with the outcomes (see Slade and Prinsloo 2013:14). To ignore information which might help to improve the outcomes seems to be shortsighted in the extreme since higher education is accountable to the stakeholders, government and the students themselves (Slade and Prinsloo 2013:14), If used for this purpose, learning analytics can penetrate the fog that has settled over much of higher education (Long and Siemens 2011:40).Therefore, Markham and Buchanan (2012:4) argues that researchers need to balance the rights of the subjects (as authors, research participants or people) with the social benefits of research and the rights to conduct research. In different contexts the rights of the subjects might outweigh the benefits of the research.

Signals – the affordances for an early warning system in higher education

Purdue University developed an early warning system Signals, to improve student retention. Such a system can be useful, but the efficiency of Signals have been analysed in a series of blog entries and no causal connection could be found between students who have used the system and their tendency to stick with their studies (Strausheim 2013)

Signals combines demographic information with online engagement to produce red, yellow or green light to indicate to students how well they are participating in their courses. The information is also provided to the lecturers so that they can provide help before students drop out or fail the course (Strausheim 2013). The method to structure an early warning system has permeated the industry and a few software packages are available such as Course Signals (Ellucian),  Retention Centre (Blackboard) and Student Success System (Desire2Learn). Although early warning systems have been developed based on Purdue University’s claim that it reduced dropout rates, research findings do not validate this claim.

Pistilli, research scientist at Purdue claimed that two Signals-enabled courses offered at Purdue University increased students’ six year graduation rate by 21.48%. This claim is not supported by two other researchers.

Caulfield, Director of blended and networked learning at Washington State University compared the retention rates of the 2007 and 2009 cohort enrolled for Signals courses and suggested that the data Purdue described as data analysis just measured how many courses the students were enrolled for (Strausheim 2013). According to Caulfield the students took more signals courses because they persist, rather than persisting because they were taking Signals courses.

Essa, the vice president of research and development of McGraw-Hill Education supported this finding. According to Essa, who simulated the data, the retention gain is not a real gain (causal) but an artefact of the fact that students who are staying longer at university are likely to graduate.

Researchers do not question the need to integrate early warning systems such as Signals, they only question the claim that early warning systems can improve student retention (Strausheim 2013). Research findings do not support the claim that these systems improve retention, but these systems do not face and existential crisis according to Essa, who helped to design Student Success System for Desire2Learn. According to Essa the aim of early warning systems is to make sure that students are performing well. Therefore, the focus should be on investigating the impact of the early warning system on learner results rather than retention.

it is not sufficient to investigate the impact of early warning systems on student retention. Lecturers need to be able to use the information to intervene by providing Just-In-Time-Teaching while students are taking the course. One of the reasons why staff and lecturers do not take this route, is that it can take months before ethical clearance and permission to use staff and student data are given. In order to report on the success or failure of an early warning system, the following questions need to be asked:

  • What is the impact of the early warning system on student performance during the course?
  • How did the lecturers react on the information provided by the early warning system? In other words, did they provide remedial activities in order to improve student performance? Did they provide support?
  • How did the students react on the fact that their lecturers were informed about non-completions of learning activities? Did they appreciate it or did they feel that their privacy was invaded?
  • What is the relationship between course participation and student success, in other words, do students, who complete all learning activities performa better than those who don’t? If not, the following question can be asked:
  • How effective is the structure of the course? In other words, are the students guided through small steps from unfamiliar with course content to being competent?
  • How can the course be improved to improve student success?

These questions might ignite more questions that can be asked in order to uderstand how early warning systems such as Signals can improve success rates in higher education. To me, it is more of an ethical issue to have the information available, but not acting on it, than not having permission to collect the data that can improve the success of my students while the lecturer is in the position to intervene in order to increase student success.

Skinner’s Teaching Machine related to current trends in education

The concept of automated teaching dates back to the 1950’s when skinner developed a Teaching Machine to improve student success. The teaching machine could be used by individual students in any situation where they are using words or symbols during the learning process. Skinner believed teaching machines can have a dramatic effect on teaching, yet, 70 years later teachers and lecturers are not (yet) replaced by educational technologies but the idea of technology-supported teaching resurfaced in the format of Intelligent Tutoring Systems.

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Mendeley 06a – How to use Mendeley for referencing (Apple)

The basic reason why I want to use this technology, is to cite references in text and to create bibliographies using the correct style. These steps can be followed for this purpose. Since the process differs in the case of MAc and Windows operated systems, I will provide steps for both these operating systems.

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