My current PLN: What networks, tools and communities should I use?
At present, my PLN is mainly based on four commonly used platforms: WeChat, TikTok, Little Red Book (Little Red Book) and Bilibili.com. I don’t browse these platforms casually; on the contrary, I gradually develop my own learning process: first, I collect information from multiple sources on public platforms, then return to the private field for discussion and verification, and finally use AI to summarize and structure.
WeChat (Private Domain Polish Flower Source): I will discuss “hot topics I see” and “uncertain points” in my circle of acquaintances or groups. Common topics include social issues and policy discussions related to education, public communication and public opinion case studies, and the exchange of learning resources. The advantage of WeChat is that the trust cost is low and the feedback is fast; the disadvantage is that the information source is easily homogenized.
TikTok (trend input): I use it to observe the content of public discussion, and often read news interpretation, short comments on social issues, professional experience sharing and educational hot topics. However, I am cautious about emotional hype and misleading editing, so I usually don’t forward content easily.
Small Red Note (experience and resources): It is more like an “experience database”. I browse it for learning methods, resource collation, career preparation and education-related experience sharing. However, I also remind myself that experience posts can be clues, not evidence.
Bilibili (Systematic Learning): It is closer to the long content learning platform. I watch education/social science lectures, popular science articles on public policies and social operation mechanisms, and content related to artificial intelligence to understand how technology changes the production and dissemination of knowledge.
Career goals: Why do education-related occupations need PLN?
I hope to enter public sector positions related to education in the future (such as policy implementation, rulemaking or public communication). This means that my public learning network (PLN) can not only follow the trend, but must support three points in the long run:
Understand different stakeholders in education issues (students, teachers, parents, schools, social organizations)
Promote information from views to verifiable evidence (research, policy documents, authoritative sources)
Have public communication skills (how to explain policies, answer questions and avoid misleading)
Putting academic research together with personal experience: my contradictory attitude towards artificial intelligence is not uncommon.
The research of Estaiteyeh and Mindzak points out that prospective teachers often face a “double identity paradox”: they are both students who will use generative artificial intelligence and future teachers, and must be responsible for guiding and managing artificial intelligence; they admit that generative artificial intelligence is almost It can be avoided, but its value, use and ethical/teaching impact are still uncertain. The study also emphasizes that this is not a marginal problem, but a profound change in the teaching structure: knowledge production, evaluation and teaching practice are increasingly mediated by algorithms and artificial intelligence. Associate teachers are often worried about students’ abuse (plagiarism, superficial participation, decline in critical thinking), and also hope to learn practical strategies (using artificial intelligence to design evaluation, assist scoring and detect tool abuse).
This research is highly consistent with my experience: I mainly use artificial intelligence for learning and summary (organizing key points, structured fragmented information, and comparing views from different sources). Although it does improve efficiency, it also reminds me that taking AI output as the final answer will turn learning into “faster and more superficial understanding”. Therefore, I set a rule for myself: AI is responsible for the organization, but the key conclusions must be traced back to verifiable sources (papers, official documents, authoritative reports); otherwise, it only makes unreliable content look more “real”.
The impact of PLN + AI on fairness and accessibility
From the perspective of fairness and accessibility, AI and PLN “lower the entry threshold” and “create new barriers” at the same time:
Improve accessibility: artificial intelligence helps to understand complex information (summary, structured, language-assisted); public platforms also make information that used to circulate only in professional circles visible to a wider audience.
Create inequality: algorithm recommendations will make people fall into the echo chamber; the ability to use artificial intelligence itself may become a new digital divide; the quality of platform content varies greatly, and “accessible” is not the same as “trustworthy”.
Therefore, I think AI improves efficiency, but does not automatically improve quality. This also explains the reality of “uncertainty” and “lack of consensus framework” mentioned in the study: the system level is still adapting to change.
Critical evaluation: My advantages and disadvantages of PLN (including AI)
Advantages:
Fast input speed and wide coverage (TikTok/Xiaohongshu)
More complete input level (see Bilibili + WeChat discussion for verification for details)
Artificial intelligence helps me transform fragmented information into structured understanding (provided for follow-up verification)
Weakness:
The chain of evidence is unstable: many experience posts, the source is unknown
Eso room risk: algorithms may reinforce bias
Lack of professional community connection: at present, it is biased towards the mass platform; more opportunities to enter the education policy/teacher’s professional community are needed.
PLN in the context of Canadian education: I want to upgrade “personal browsing” to “professional network”
In the field of education in Canada, educators and educational leaders often expand their professional learning networks through online writing and public communication. Chris Kennedy’s blog “Yes Culture” (Education Leaders in West Vancouver School District) is a typical example: through continuous writing and dialogue, educational discussions are brought into the public sphere, allowing them to examine, supplement and improve views. At the same time, the Canadian Federation of Teachers (CTF) promotes the National Professional Learning and Development Network (PLDN), emphasizing the connection between provincial teacher organizations and supporting the continuous professional development of teachers.
These examples made me realize that PLN is not just “receiving information” on the platform; it can be organized, maintained for a long time, and become a part of career growth.
How can I improve PLN next:
In order to make my public education network closer to the direction of the public sector, I will do three things:
Improve information sources: pay attention to Canadian education leaders, teacher organizations, policies and research resources, rather than relying solely on algorithm recommendations.
Establish the boundaries of artificial intelligence: Artificial intelligence will be used for summary and comparison, but key conclusions must be supported by verifiable sources; do not regard artificial intelligence as authority.
Active diversification + regular review: check whether the information source is too single (language field, position, region), introduce different background voices, and insist on taking verifiable facts as the bottom line.
Reference
Estaiteyeh, M., & Mindzak, M. (2025). Building AI Literacy in Pre-Service Teacher Education in Canada.
Chris Kennedy. Culture of Yes . https://cultureofyes.ca/ Canadian Teachers’ Federation.
Professional Learning and Development Network .https://www.ctf-fce.ca/blog-perspectives/new-professional-learning-and-development-network-to-benefit-teachers-across-the-country/