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Why these stages matter

HCD practitioners can better understand their own learning process and set appropriate expectations if they know the typical stages of the learning journey. 

NN/g concluded that:

• Most learning journeys feel frustrating at some point. Having insight into the HCD learning journey and the end goal can provide encouragement during “what’s the point” moments. If you’re learning HCD independently, awareness of the journey can help you feel less alone.
• Identifying one’s current phase can help predict future progress, staying focused on the goals of the current learning phase rather than jumping ahead. Jumping ahead runs the risk of creating experiences that may be confusing, and thus less motivated to continue to learn. 

Course facilitators (or managers or mentors), must empathize, create an effective HCD learning experience for others, and enable sustainable, long-term success. 

• Understanding that different people will be at different stages in the learning process is a key part in being an effective educator. It allows for the delivery of effective learning experiences without overwhelming the audience with too much complexity and also preemptively mitigate learners’ pain points at each phase. 

Educating and activating a group of people takes a lot of resources (time, money, and effort). The education process should be intentionally designed, in order to maximize resources and return on investment. Mapping participants’ phases and their progression through the learning journey allows an educator to benchmark progress, and indirectly, success of the training. 

As practitioners progress through the stages, their mastery increases in a nonlinear fashion — experiencing fluctuations due to various factors, especially, lack of self-confidence. Note that mastery is a combination of competence and confidence; both are required to effectively use HCD. If a practitioner is good but still feels insecure, they won’t deviate from the strict steps of HCD and won’t teach others.  The goal is to create alignment between competence and confidence in order to master HCD.

The Structure

Rather than thinking of each phase as a discrete checklist, NN/g created a three-component framework for characterizing each learning stage: criteria, primary activities, and educator goals.

1. Criteria are observable qualities that can help the learner (or an external observer, such as a trainer) identify the learner’s current stage along the learning journey. It includes awareness of one’s own competence, level of exposure, and confidence.
2. Primary activities are the learner’s actions and use of HCD methodologies.
3. Educator goals and obstacles summarize learner’s pain points at any given stage and corresponding educator goals that can help learners overcome them. 

Phase 1: Newcomer 

This phase is the first in the learning journey. For the majority of HCD practitioners, this exposure occurs via a university or institution, a place of work, or an online resource. The amount of time spent at this first stage depends on how motivated the learner is. Interestingly, many practitioners immediately perceive HCD as useless and never leave this stage.

Criteria

Individuals in this stage have been introduced to HCD, but have limited experience with it. Practitioners in this phase fall into 2 buckets:

1. Individuals who are committed to learn HCD
2. Individuals who are not interested to learn more about HCD. They’ve been exposed to it, but that is where their learning journey halts. Newcomers may remain in this stage indefinitely until they encounter a deeper exposure to HCD that broadens their perspective, experience, or acceptance. 

Newcomers’ knowledge is minimal; they have a surface-level understanding of HCD, often rooted in the definition they received during their first exposure. They may be able to provide a definition, but are not familiar with the details of a framework or its value. They have topical associations with HCD — sticky-notes, phase models, and whiteboards. Newcomers are unaware of their HCD incompetence. In other words, they don’t yet know what they don’t know.

Primary Activities

Newcomers’ primary goal is to understand the basics — what HCD is and why it’s useful. Often, this stage’s activities are self-initiated: browsing articles, reading books, or signing up for a course. In other cases, HCD is learned by necessity or requirement at work or school through onboarding programs, collaborative workshops, required courses, or mandated trainings. Most newcomers have not yet actively practiced HCD activities. If they have practiced HCD at all, their participation is limited and surface-level. 

Educator’s Goals and Obstacles

The goal of an HCD educator at this stage is to communicate the purpose and potential value of HCD and to motivate the newcomer to pursue learning, then make time for it and move on to the next phases. Common obstacles are overcoming learners’ negative sentiments: annoyance with “yet another thing to learn,” unsuccessful previous attempts or experiences, capped bandwidth, and realization of their own limits (in this case, how little they know about HCD). 

Phase 2: Adopter

Individuals in phase 2 have adopted HCD and begun to practice it. They may have had some ups and downs in their limited experience with HCD. It is common for adopters to flip-flop between overconfidence and self-doubt and to feel both confused and successful at the same time. Successful adopters have discovered how relevant HCD is to their work or life and, thus, make a commitment to continue learning.

Criteria

Increased (passive or active) exposure and familiarity with HCD has made adopters aware of their knowledge limits. They understand the potential of HCD, but still have a lot to learn. Adopters have invested time, effort, and energy into HCD and have started applying it to their work with mixed success. The commitment to HCD at this phase can be self-initiated or dictated by an authority with an invested interest (leadership, organization, or supervisor). 

Primary Activities

Adopters practice HCD in a linear way — by the book. They rely heavily on checklists — for example an HCD Phases Model, as well as for the activities associated with each of its steps. Many adopters lean towards a prescribed, branded version of HCD, often provided by their institution, company, or a reputable external organization.  

It is common for HCD practitioners to encounter failure in this phase — especially if they are learning predominately on their own — because of their incomplete understanding of the HCD framework. Common types of failure include jumping to conclusions, using the wrong activity at the wrong time, and lack of buy-in or support from others. These failures push some practitioners to abandon HCD altogether. However, most learning in this phase occurs through failure. Practitioners who embrace failure tend to develop a better understanding of HCD in future phases.

Some adopters might learn primarily by actively participating in HCD training, coaching and activities together with experienced HCD practitioners. While this group of adopters may not have the opportunity to experience a sense of failure because of the support received from their peers, it is still likely they will question the value and legitimacy of HCD from time-to-time.   

Educator’s Goals and Obstacles

Adopters are on the bike, but still need training wheels and coaching. Adopters’ confidence drops as they realize the indirect ways in which HCD can be applied and how much they have to learn — for example, how straightforward they originally thought the process was versus how abstract (and potentially overwhelming) it really is. The goal of the educator at this stage is to help learners through hands-on practice and assistance until they can comfortably use HCD on their own. Many individuals can become confused in this phase when they cannot make a direct connection to the relevance of HCD. Thus, it is imperative that adopters find relevance and application to their everyday work.

Phase 3: Leader 

This is the proficiency stage of HCD. Leaders can articulate HCD succinctly to others, steadily growing their confidence, with varied experiences and continued exposure. Leaders take an active, independent role in their learning journey and begin to think adaptively about HCD; starting to explore new applications and may even have established a reputation as a subject matter expert. 

Criteria

Leaders practice HCD with general ease, confidence, and independence. Leaders become more and more aware of their new knowledge and comfort as they mature through this phase. They often teach others earlier in the learning journey. They are able to consistently and somewhat adaptively perform HCD activities without thinking too much about them. Leaders don’t try to apply HCD by the book, rather use it as needed depending on the goals. 

Primary Activities

HCD practitioners in this phase lead HCD activities with others or perform HCD without coaching, but still apply preparation and focus. While they were previously participants, they now facilitate, initiate, and even advocate for collaborative HCD activities. Activities that leaders are involved in gradually increase in complexity, ranging from involving users in learning opportunities to fostering stakeholders into the process and prototyping. 

Educator’s Goals and Obstacles

The goal of the educator in this phase is to continue to instill confidence and help sustain learner commitment. The goal should be to empower leaders to transition into the role of HCD educators and facilitators. As much as they’ve progressed, they still may not be aware of weaknesses or potential improvements (even though they often recognize a mistake after they made it). Promoting reflection in this phase is the key to helping leaders continue to grow (and progress to grandmasters). They must take an active role in adapting the HCD practice to fit their contextual goals and needs, be sustainable over time, and maximize potential benefits.  

Phase 4: Grandmaster

If you are familiar with the game of chess, the title of grandmaster is only given to the most exceptional players—those who have spent countless hours perfecting their skills and techniques.

HCD practitioners at this stage have not only become teachers of HCD, but create new ways of applying it, thinking about it, and adding to it. The practice of HCD is so embodied in their behavior that they seldom have to think about applying it. Grandmasters view HCD as a flexible, dynamic toolkit. They’ve long departed from the concept of a prescribed process and rather view it as scaffolding to solve both organizational (often internal) and end-user (external, product-related) problems. However, this phase doesn’t come without downsides. Grandmasters are more likely to doubt HCD than leaders, often when early-stage learners fall victim to mismanaged HCD marketing and thus misinterpret, misapply, or undercut the practice as a whole. 

Criteria

Grandmasters’ defining characteristic is the ability to critically reflect on their HCD practice. This enables them to judge what is useful and potentially depart from the traditional ways and activities of HCD. Grandmasters also know how to help others to this same stage of enlightenment. Grandmasters are aware of their competence. They have an in-depth, intuitive understanding and can blend HCD skills together to meet specific needs. 

Primary Activities

Traditional HCD activities are still used by grandmasters, but are altered, adapted, and applied in complex ways, depending on the goal, audience, and potential obstacles. Grandmasters don’t stick to prescribed or branded versions of HCD and more often pull tools and/or activities from other realms, like service design and business strategy. While basic HCD activities are still carried out in this phase, they differ from those in earlier stages because they are inputs or alignment strategies for more complex, involved activities (compared to previous stages where the basic activities are the end goal). 

Educator’s Goals and Obstacle

Grandmasters have very likely surpassed their original teachers. Their goal becomes not just activating and educating individual learners, but rather organizations as a whole. As practitioners themselves, grandmasters face an increasing likelihood of (re)questioning the value of HCD. Increased knowledge and mastery are a blessing and curse; this pessimistic view is often rooted in the realization of what HCD can and cannot solve (contrary to earlier naive ideas that HCD can be a cure-all). However, even grandmasters can get better, by self-reflection, by learning from their peers, and also by learning from their juniors: one of the skills of supreme mastery is the ability to discern which of the hundreds of ideas generated by eager newcomers is actually a stroke of genius.

Other Considerations 

• Trained designers experience the HCD learning journey too, just differently. Many designers view HCD as simply a way to articulate and communicate a creative approach to problem solving. Thus, many designers are likely to feel as if they bypassed this learning journey altogether because this is how they instinctively think. However, designers experience this learning journey too, albeit much earlier in their education or career, and likely not packaged or branded as HCD. This does not mean that all grandmasters are designers, but rather that many successful designers likely are. 
• Individual practitioners can be at multiple levels at the same time. Some skills may fall into one phase, while others into a lower different phase. For example, a practitioner’s mindset and reflection may fall into Grandmaster, while their hands-on experience and exposure to activities into Leader. The goal is to identify this imbalance and invest in experiences that bolster weaker dimensions of our practice. 

The HCD learning journey is a high-level, distilled representation of the most common learning phases observed in the NN/g research. Learning and teaching HCD is messy; not all experiences will fit squarely into this model. 

Regardless, it is imperative to frame and articulate learning HCD as an experiential journey. Doing so can help all practitioners become more effective learners and educators. Learners can gain insight and awareness into the greater journey and goals, while educators can thoughtfully and successfully execute the HCD learning experience they aim to create.  

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For instance, let’s say a religious conservative researcher is conducting a study on the effects of alcohol. If the researcher’s conservative, anti-alcohol beliefs prompt him or her to create a biased survey or have sampling bias, then this is a case of research bias. 

Types of Research Bias 

Design Bias

Design bias has to do with the structure and methods of your research. It happens when the research design, survey questions, and research method is largely influenced by the preferences of the researcher rather than what works best for the research context. 

In many instances, the poor research design of a systematic investigation can infuse bias into your research process. Research bias also happens when the personal experiences of the researcher influence the choice of the research questions and methodologies. 

Example of Design Bias 

• A researcher who is involved in the manufacturing process of a new drug may design a survey with questions that only emphasize the strengths and value of the drug in question. 

Selection or Participant Bias

Selection bias happens when the research criteria and study inclusion method automatically exclude some part of your population from the research process. When you choose research participants that exhibit similar characteristics, you’re more likely to arrive at study outcomes that are  one-dimensional. 

Selection bias manifests itself in different ways in the context of research. Inclusion bias is particularly common in quantitative research and it happens when you select participants to represent your research population while ignoring groups that have alternative experiences. 

Examples of Selection Bias 

1. Administering your survey online; thereby limiting it to internet savvy individuals and excluding members of your population without internet access. 
2. Collecting data about parenting by only surveying or interviewing a mother’s group. The findings in this type of research will be biased towards mothers while excluding the experiences of fathers. 

Publication Bias

Peer-reviewed journals and other published academic papers, in many cases, have some degree of bias. This bias is often imposed on them by the publication criteria for research papers in a particular field. Researchers work their papers to meet these criteria and may ignore information or methods that are not in-line with them. 

Example of Publication Bias 

• Research papers in quantitative research are more likely to be published if they contain statistical information. On the other hand, non-publication in qualitative studies is more likely to occur because of a lack of depth when describing study methodologies and findings are not presented. 

Analysis Bias

This is a type of research bias that creeps in during data processing. Many times, when sorting and analyzing data, the researcher may focus on data samples that confirm his or her thoughts, expectations, or personal experiences; that is, data that favors the research hypothesis. 

This means that the researcher, albeit deliberately or unintentionally, ignores data samples that are inconsistent and suggest research outcomes that differ from the hypothesis. Analysis bias can be far-reaching because it alters the research outcomes significantly and provides a false presentation of what is obtainable in the research environment. 

Example of Analysis Bias 

• While researching a new medication, a researcher pays attention to data samples that reinforce the negative effects of the medication while ignoring data that suggests the positives.

Data Collection Bias

Data collection bias is also known as measurement bias and it happens when the researcher’s personal preferences or beliefs affect how data samples are gathered in the systematic investigation. Data collection bias happens in both qualitative and quantitative research methods. 

Examples of Data Collection Bias

1. In quantitative research, data collection methods can occur when you use a data-gathering tool or method that is not suitable for your research population. For example, asking individuals who do not have access to the internet, to complete a survey via email or your website. 
2. In qualitative research, data collection bias happens when you ask bad survey questions during a semi-structured or unstructured interview. Bad survey questions are questions that nudge the interviewee towards implied assumptions. Leading and loaded questions are common examples of bad survey questions. 

Procedural Bias

Procedural is a type of research bias that happens when the participants in a study are not given enough time to complete surveys. The result is that respondents end up providing half-thoughts and incomplete information that does not provide a true representation of their thoughts. 

There are different ways to subject respondents to procedural respondents. For instance, asking respondents to complete a survey quickly to access an incentive, may force them to fill in false information to simply get things over with. 

Example of Procedural Bias

• Asking employees to complete an employee feedback survey during break time. This timeframe puts respondents under undue pressure and can affect the validity of their responses. 

Furthermore, specific biases can be introduced into research based on whether you are specifically conducting either quantitative or qualitative research. 

Bias in Quantitative Research

In quantitative research, the researcher often tries to deny the existence of any bias, by eliminating any type of bias in the systematic investigation. Sampling bias is one of the most common types of quantitative research bias, driven by the samples you omit and/or include in your study. 

Types of Quantitative Research Bias

Design Bias

Design bias occurs in quantitative research when the research methods or processes alter the outcomes or findings of a systematic investigation. It can occur while the experiment is being conducted or during the analysis of the data to arrive at a valid conclusion. 

Many times, design biases result from the failure of the researchers to take into account the likely impact of the bias in the research they conduct. This makes the researcher ignore the needs of the research context and instead, prioritize his or her preferences. 

Sampling Bias

Sampling bias in quantitative research occurs when some members of the research population are systematically excluded from the data sample during research. It also means that some groups in the research population are more likely to be selected in a sample than the others. 

Sampling bias in quantitative research mainly occurs in systematic and random sampling. For example, a study about breast cancer that has just male participants can be said to have sampling bias since it excludes the female group in the research population. 

Bias in Qualitative Research

In qualitative research, the researcher accepts and acknowledges the bias without trying to deny its existence. This makes it easier for the researcher to clearly define the inherent biases and outline its possible implications while trying to minimize its effects. 

Qualitative research defines bias in terms of how valid and reliable the research results are. Bias in qualitative research distorts the research findings and also provides skewed data that defeats the validity and reliability of the systematic investigation. 

Types of Bias in Qualitative Research

Bias from Moderator

The interviewer or moderator in qualitative data collection can impose several biases on the process. The moderator can introduce bias in the research based on his or her disposition, expression, tone, appearance, or relation with the research participants. 

Biased Questions

The framing and presentation of the questions during the research process can also lead to bias. Biased questions like leading questions, double-barreled questions, negative questions, and loaded questions, can influence the way respondents provide answers and the authenticity of the responses they present. 

The researcher must identify and eliminate biased questions in qualitative research or rephrase them if they cannot be taken out altogether. Remember that questions form the main basis through which information is collected in research and so, biased questions can lead to invalid research findings. 

Biased Reporting

Biased reporting is yet another challenge in qualitative research. It happens when the research results are altered due to personal beliefs, customs, attitudes, culture, and errors among many other factors. It also means that the researcher must have analyzed the research data based on his/her beliefs rather than the views perceived by the respondents. 

Bias in Psychology

Cognitive biases can affect research and outcomes in psychology. For example, during a stop-and-search exercise, law enforcement agents may profile certain appearances and physical dispositions as law-abiding. Due to this cognitive bias, individuals who do not exhibit these outlined behaviors can be wrongly profiled as criminals. 

Bias in Market Research

There are 5 common biases in market research – social desirability bias, habituation bias, sponsor bias, confirmation bias, and cultural bias. Let’s find out more about them.

• Social desirability bias happens when respondents fill in incorrect information in market research surveys because they want to be accepted or liked. It happens when respondents are seeking social approval and so, fail to communicate how they truly feel about the statement or question being considered. 

A good example will be market research to find out preferred sexual enhancement methods for adults. Some persons may not want to admit that they use sexual enhancement drugs to avoid criticism or disapproval.

• Habituation bias happens when respondents give similar answers to questions that are structured in the same way. Lack of variety in survey questions can make respondents lose interest, become non-responsive, and simply regurgitate answers.  

For example, multiple-choice questions with the same set of answer options can cause habituation bias in your survey. What you get is that respondents just choose answer options without reflecting on how well their choices represent their thoughts, feelings, and ideas. 

• Sponsor bias takes place when respondents have an idea of the brand or organization that is conducting the research. In this case, perceptions, opinions, experiences, and feelings about the sponsor may influence how they answer the questions about that particular brand. 

For example, let’s say ACME App Developers (sponsor) is conducting research about their users' preferred online tools. Respondents may mention the sponsor of the survey (ACME App Developers) as their preferred app developer out of obligation; especially when the survey has some incentives.

• Confirmation bias happens when the overall research process is aimed at confirming the researcher’s perception or hypothesis about the research subjects. In other words, the research process is merely a formality to reinforce the researcher’s existing beliefs. 

Electoral polls often fall into the confirmation bias trap. For example, civil society organizations that are in support of one candidate can create a survey that paints the opposing candidate in a bad light to reinforce beliefs about their preferred candidate. 

• Cultural biasarises from the assumptions we have about other cultures based on the values and standards we have for our own culture. For example, when asked to complete a survey about our culture, we may tilt towards positive answers. In the same vein, we are more likely to provide negative responses in a survey for a culture we do not like. 

So now that you know what types of bias commonly exist in user research efforts, how do you identify and avoid them? Here are some tips...

How to Identify Bias in a Research

1. Pay attention to research design and methods. 
2. Observe the data collection process. Does it lean overwhelmingly towards a particular group in the survey population? 
3. Look out for bad survey questions, such as loaded questions and negative questions. 
4. Observe the data sample you have to confirm if it is a fair representation of your research population.

How to Avoid Research Bias 

1. Gather data from multiple sources: Be sure to collect data samples from the different groups in your research population. 
2. Verify your data: Before going ahead with the data analysis, try to check-in with other data sources, and confirm whether you are on the right track. 
3. If possible, ask research participants to help you review your findings: Ask the people who provided the data whether your interpretations seem to be representative of their beliefs. 
4. Check for alternative explanations: Try to identify and account for alternative reasons why you may have collected data samples the way you did. 
5. Ask other members of your team to review your results: Ask others to review your conclusions. This will help you see things that you missed or identify gaps in your argument that need to be addressed.

Conclusion 

Biased research has very little to no value. Such studies produce distorted impressions and present false conclusions. Often, the findings of biased research can impede important decision-making processes and may negatively impact the people or businesses that rely on them. 

Acknowledging one’s susceptibility to bias and understanding its many forms will help you design a balanced studies. As long as you know what types of bias in research to look for and how to eliminate them, you can produce valuable results.This article is based on a research study conducted by the Nielsen Norman Group. Originally published January 2021. 

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